From Frames to Inference

Nancy Chang, Srini Narayanan, and Miriam R.L. Petruck International Computer Science Institute

1947 Center St., Suite 600, Berkeley, CA 94704

nchang,miriamp,snarayan ¡ @icsi.berkeley.edu

Abstract money ($1000) to another (Jerry) in exchange for some goods (a car) – but differ in the perspective This paper describes a computational they impose on the scene. formalism that captures structural rela- The shared inferential structure of verbs like buy tionships among participants in a dy- and sell is captured in FrameNet by the COMMERCE namic scenario. This representation is frame, which is associated with a set of situational used to describe the internal structure of roles, or frame elements (FEs), corresponding to FrameNet frames in terms of parameters event participants and props. These FEs are used for active event simulations. We apply our as annotation tags for sentences like those in (1), formalism to the commerce domain and yielding, for example: show how it provides a flexible means of handling linguistic perspective and other Buyer Goods challenges of semantic representation. (2) a. [Chuck] bought [a car] [from Jerry]Seller [for $1000]Payment. 1 Introduction b. [Jerry]Seller sold [a car]Goods [to Chuck]Buyer [for $1000]Payment. The development of lexical semantic resources is widely recognized as a prerequisite to progress in FE tags act as a shorthand that allows diverse verbs scalable natural language understanding. One of the to tap into a common subset of encyclopedic knowl- most semantically sophisticated efforts in this direc- edge. Moreover, regularities in the set of FEs real- tion is FrameNet (Baker et al., 1998; Fillmore et al., ized with specific lexical items can be taken as cor- 2001), an online lexical resource1 designed accord- related with their favored perspective. ing to the principles of frame semantics (Fillmore, 1985; Petruck, 1996). FrameNet takes as founda- A significant gap remains, however, between the tional the assumptions that (1) lexical items draw unstructured and intuitively chosen tag sets used in on rich conceptual structures, or frames, for their FrameNet and a formal characterization of the inter- meaning and function; and (2) conceptually related related actions and relations holding among them. lexical items may foreground different aspects of The explicit representation of such frame semantic the same background frame. Verbs involved with information is needed for FrameNet’s potential use commercial events serve as canonical examples: in text understanding and inference (Fillmore and Baker, 2001) to be fully realized. In this paper we (1) a. Chuck bought a car from Jerry for $1000. attempt to bridge the gap by defining a formalism b. Jerry sold a car to Chuck for $1000. that unpacks the shorthand of frames into structured c. Chuck paid Jerry $1000 for a car. event representations. These dynamic representa- d. Jerry charged Chuck $1000 for a car. tions allow annotated FrameNet data to parameter- e. Chuck spent $1000 on a car. ize event simulations (Narayanan, 1999b) that produce fine-grained, context-sensitive inferences. We The sentences in (1) might describe the same inter- illustrate our formalism for the COMMERCE frame action – in which one individual (Chuck) transfers and show how it can account for some of the wide- 1http://www.icsi.berkeley.edu/framenet/ ranging consequences of perspective-taking.

Figure 1: Results of a query on the FrameNet COMMERCE frame, showing annotated data for the verb buy.

2 The FrameNet COMMERCE frame (e.g., many but not all appear in the ditransitive construction), and not all of them license the expression The FrameNet project has thus far produced two of all FEs (e.g., spend rarely appears with the Seller). databases: a collection of approximately 80 frames Also, some FEs are realized in different ways for with frame descriptions, chosen to cover a broad different verbs: the pattern of appearance with from- range of semantic domains; and a hand-annotated or to- headed PPs differs for buy and sell, and for- dataset of about 50,000 sentences from the British headed PPs may mark either the Payment (for buy National Corpus (Baker et al., 1998). The databases and sell) or the Goods (for pay). document both syntactic and semantic behavior of a Much of this diversity has been attributed to dif- wide variety of lexical items (or lemmas) and thus ferences in perspective, but the complex connec- have the potential to allow corpus-based techniques tions among perspective, argument structure and FE to be applied to semantically oriented tasks.2 realization have been difficult to explicate. One ap- The current release of the FrameNet databases3 proach is to distinguish the COMMERCE frame from defines a COMMERCE frame with frame elements other perspectivized frames exhibiting more con- including the familiar Buyer, Seller, Payment and sistent behavior; proposals along these lines differ Goods, along with several other FEs needed to cover in their criteria for making these divisions and the the data. The frame includes 10 verbs relevant to relationships among the resulting frames.4 commercial transactions, for a total of 575 anno- Our proposal likewise imposes additional struc- tated sentences. Figure 1 shows a sampling of data ture on the COMMERCE frame to reflect both annotated with respect to the COMMERCE frame. perspective-neutral and perspectivized situations. The COMMERCE frame verbs exhibit relatively But for current purposes, we concentrate on cap- greater variety in argument structure possibilities turing perspectival effects on inference in discourse 2See (Gildea and Jurafsky, 2000) for some promising ini- tial work in applying statistical techniques to the FrameNet 4FrameNet II is currently considering a reorganization database to automatically label frame elements. scheme along these lines. Gawron (ms.) and Hudson (in press) 3Throughout the paper we refer to data from FrameNet I; an address these and related issues, both arguing against handling interim release of FrameNet II data is expected soon. perspective solely with multiple inheritance.

2 interpretation. Our structures are thus designed a predicate on accessible structures.6 The keyword to support dynamic inferences about interrelated self refers to the structure being defined, which we events and actions, and not specifically to reflect FE can consider a special kind of role. We use ‘//’ to realization patterns. introduce italicized comments.

We take the original COMMERCE frame as ¤ schema £ name

our starting point and deﬁne the interrelationships ¥ ¤ subcase of £ schema

present among its FEs; the resulting event represen- ¦ evokes

¤ £ ¤©¨

tation can license inferences for sentences like those £ schema as local-name

in the annotated FrameNet data. We assume that roles

¤ £ local-role

any frame reorganization scheme (as well as any

£ ¤ £ ¤

local-role : restriction

¤£ ¤

method for labeling roles in novel text) will deﬁne £ local-role role

¤£ ¤ £ ¤

a mapping to the original FEs and thus could be in- £ local-role role : restriction

tegrated with our dynamic representations within a constraints

¤£ ¤

larger language understanding enterprise. £ role role

¤ £ ¤ £ phase :: condition 3 Structured event representations Figure 2: Schema definition formalism. In this section, we present a formal specification The first line names the schema being defined. used for mapping the flat set of FEs in COMMERCE onto explicitly structured event representations that The next few lines (subcase of and evokes) indi- characterize commercial transactions. Our repre- cate how this schema relates to other schemas. The sentation is based on the Embodied Construction subcase relation defines a lattice of schemas, with Grammar (ECG) formalism (Bergen and Chang, the local schema inheriting all roles and constraints. 2002). As in that work, we assume that understand- The evokes relation also makes the specified struc- ing an utterance involves the evocation of a com- tures and constraints of the evoked schema (re- plex network of conceptual schemas and the mental ferred to within the current definition using a £ local- simulation of these schemas in context to produce name ¤ ) locally accessible, but it implies neither full a rich set of inferences.5 inheritance of the evoked schema’s roles nor con- Among the features of the ECG schema formal- tainment in either direction. ism that we exploit to represent commercial transac- The indented block labeled roles lists and con- tions are (1) the ability to flexibly evoke and relate strains the schema’s local roles, which are equiv-

multiple schemas; and (2) the ability to assert dy- alent to frame FEs. Roles are declared with a lo- ¤ namic conditions that apply to specific event stages. cal name ( £ local-role ) and may be accompanied by We rely heavily on the fact that schemas can be in- type restrictions (indicated with ‘:’) and/or identi- terdefined in our eventual representation of differ- fication (or binding) constraints (‘ ! ’). The lat- ences in perspective. ter (which may also appear in the constraints block) We briefly describe the schema definition lan- causes roles and constraints to be shared between its guage shown in Figure 2, deferring additional de- arguments, similar to unification or coindexation in tails for the examples. Keywords are shown in other frameworks (Pollard and Sag, 1994). bold; a left square bracket ([) marks optional blocks; The final constraint type allowed is a simulation constraint, which uses the ‘::’ notation to assert and curly braces ( ¡ ) enclose a set of options for

the statements that may appear (possibly multiple that some condition must hold (or not) at a particular ¤ phase of simulation (referred to as £ phase ). These times) in the block. Angle brackets ( ¢¡ ) denote a reference to an accessible structure or role, or simulation phases correspond to event stages and serve as the bridging connection to previous work 5ECG includes formalisms for both schema deﬁnitions (conceptual representations) and construction deﬁnitions 6Accessible structures include locally declared roles and (conventionalized pairings of form and meaning). Since we evoked or inherited structures, as well as any structures avail- focus here on translating frames to conceptual representations, able through their roles. Standard slot-chain notation is used to we refer only to (a version of) the schema formalism. refer to role y of a structure x as x.y.

3 on modeling event structure and linguistic aspect scribed above, thus anchoring the event to the pas- (Narayanan, 1997; Chang et al., 1998). An event sage of time; its underspecified nucleus role is con- may be viewed as having complex internal struc- strained to hold or take place during the transition ture, including a start and finish and a period during phase. The Action schema corresponds to a prototyp- which it is ongoing; at a coarser granularity it may ical situation in which an actor entity affects or ma- also be viewed as a discrete temporal chunk that nipulates an undergoer entity.7 This schema is linked takes place between two time slices. The schemas to its backgrounded temporal structure through an defined below refer to the before, after and transition evoked Event. The explicit binding of self (the Ac-

phases. (See Section 5 for more details.) The notation defined) to the nucleus role of the Event serves ¤ tion £ condition specifies a relation that holds or an as the crucial link between events and actions. This event or action that takes place during the specified link will be exploited in Section 4 to capture the re- phase (see below). lation between commercial transaction events and We now show how the formalism just defined can its various associated actions. be used to build up a set of progressively more com- schema Receive Exchange plex schemas, culminating in an schema subcase of Action that provides much of the underlying structure we evokes Possession as p

need to tackle the COMMERCE frame. For ex- roles receiver actor p.possessor

pository reasons, we omit details not relevant to received undergoer p.possession

the example. The schemas in Figure 3, for ex- constraints

ample, cast the relations of possession and causa- e.before ¢ p.holds false e.before ¢ p.holds true tion as essentially unstructured. Each schema is declared as a subcase of Relation (a general frame not schema Transfer subcase of Event Possession shown here), relating two entities (for the evokes Cause-Effect as c schema) or two events (for the Cause-Effect schema). roles act-schema : Action schema Possession schema Cause-Effect rec-schema : Receive subcase of Relation subcase of Relation agent act-schema.actor roles roles source : Entity possessor : Entity cause : Event theme rec-schema.received possesion : Entity effect : Event recipient rec-schema.receiver constraints

Figure 3: Relational schemas. transition ¡ act-schema

transition ¡ rec-schema

schema Event c.cause act-schema roles c.effect rec-schema before : Phase transition : Phase Figure 5: The Receive and Transfer schemas. after : Phase nucleus The relational and active schemas described constraints above serve as building blocks for the more com- transition ¡ nucleus plex schemas in Figure 5. We have chosen to deﬁne schema Action evokes Event as e a Receive schema – foregrounding an action deﬁned roles by a change of possession state – and a Transfer event actor : Entity undergoer : Entity – a neutral rendering of an event in which one en-

self e.nucleus tity causes another to Receive something. Note that since Event and Action are linked as shown in Fig- Figure 4: The Event and Action schemas. 7This definition applies to all schemas relevant for our ex- The schemas in Figure 4 define basic dynamic ample, though it might be more precisely called Transitive- schema types and thus pave the way for dynamic Action. Also, our role names coincide with those in Van Valin (1993) and are likewise associated with an array of prototypical constraints to be specified. The Event schema in- features. We make no theoretical claims about their grammati- cludes roles that refer to simulation phases, as de- cal status, using them here simply as simulation parameters.

4 ure 4, we could also easily define an event-based, block by two human participants and two entities. perspective-neutral version of Receive or an action- An additional agent role is not bound to any partic- based, perspectivized version of Transfer. The for- ular entity, reflecting the ability of either participant malism is flexible enough to represent any of these. (or both) to be viewed as active. The Receive schema asserts that the evoked Pos- session relation holds (or does not hold) at the sim- 4 Commercial transaction schemas ulation phases specified, and it identifies the local We are now in a position to return to the commerce receiver with both the actor (of the Action schema) domain and put our inventory of domain-general and the possessor (of the Possession schema). The event and action schemas to use. We first define Transfer schema is defined as an event in which some the Commercial-Transaction (CT) schema as a subcase action (act-schema) causes a receiving action (rec- of the Exchange schema with appropriate role iden- schema). Note that these actions are conceptually tifications and an additional type restriction on en- distinct from the nucleus role inherited from Event, tity1. The role names in this schema differ slightly although all are constrained to take place during the from those in FrameNet’s COMMERCE, reflecting event’s transition phase. The Transfer schema also has its perspective-neutral status. But given the obvi- an agent role that is constrained to be the same en- ous mapping to the FrameNet FEs, the CT schema tity as the actor of the act-schema. Importantly, the fulfills part of our original objective: based on its in- Transfer event schema makes no commitment as to herited and evoked schemas and constraints, it con- whether its agent – the entity seen as causing the cisely and precisely states the conceptual underpin- overall event – is the source, recipient or even theme. nings of the basic commercial transaction, including It is in this respect that the Transfer schema defined all entailments that are perspective-neutral. here can be considered neutral in perspective. schema Commercial-Transaction schema Exchange subcase of Exchange subcase of Event roles

roles customer participant1

participant1 : Human vendor participant2

participant2 : Human money entity1 : Money

entity1 : Entity goods entity2

entity2 : Entity goods-transfer transfer1

transfer1 : Transfer money-transfer transfer2 transfer2 : Transfer agent : Entity Figure 7: The Commercial-Transaction schema. constraints

transition ¢ transfer1 The CT schema provides the underlying in-

transition ¢ transfer2 // Constraints on transfer1: frastructure for specifying how various associated

transfer1.source participant1 schemas highlight different participants and event

transfer1.theme entity1 stages. As shown in Figure 8, we treat both Buy

transfer1.recipient participant2 // Constraints on transfer2: and Sell as subcases of Action that evoke the CT

transfer2.source participant2 schema. Both action schemas identify themselves

transfer2.theme entity2 with the ct.nucleus role (inherited from Event) and transfer2.recipient participant1 are thus (separately) constrained to take place dur- Figure 6: The Exchange schema. ing the evoked CT’s transition phase. They also both Finally, the representational machinery we have identify the undergoer with ct.goods, and the actor developed can be used to deﬁne an Exchange schema with ct.agent. The schemas impose different views (Figure 6), which provides most of the relevant con- on the same situation by virtue of a single additional straints needed for commercial transactions. It re- constraint on this latter role (which corresponds to sembles the Transfer schema in structure and is sim- the active participant in the overall CT), binding it to ilarly perspective-neutral. It includes two transfer either the ct.customer (Buy) or the ct.vendor (Sell). events that occur during the transition phase and are Pay also evokes the CT schema but is directly parameterized straightforwardly in the constraints identiﬁed with ct.money-transfer.nucleus; its actor is

5 the ct.customer (as well as the agent of the money- called executing schemas (or x-schemas), moti- transfer). This deﬁnition allows paying to refer vated by research in both sensorimotor control and speciﬁcally to a subpart of the overall commercial cognitive semantics (Narayanan, 1997). X-schemas transaction, such that its execution does not neces- are active structures that cleanly capture sequen- sarily entail the execution of the goods-transfer in the tiality, concurrency and event-based asynchronous event (i.e., you don’t always get what you pay for). control. They thus provide a cognitively moti- vated basis for modeling diverse linguistic phenom- schema Buy ena, including aspectual inference (Chang et al., subcase of Action evokes Commercial-Transaction as ct 1998), metaphoric inference (Narayanan, 1999a) roles and event-based reasoning in narrative understand-

self ct.nucleus ing (Narayanan, 1999b).

buyer actor ct.customer ct.agent goods undergoer ct.goods The model is based on the Petri net, which in its basic form is a weighted, bipartite graph consisting schema Sell subcase of Action of places (shown as circles) and transitions (shown evokes Commercial-Transaction as ct as rectangles) connected by directed input and out- roles put arcs (Murata, 1989; Narayanan, 1997). Places

self ct.nucleus

may contain tokens (i.e., they may be marked), and

seller actor ct.vendor ct.agent goods undergoer ct.goods they typically represent states, resources or conditions that apply. Transitions typically represent ac- schema Pay subcase of Action tions or events. X-schemas extend the basic Petri evokes Commercial-Transaction as ct net to include typed arcs, hierarchical control, dura- roles tive transitions, parameterization, typed (individual)

self ct.money-transfer.nucleus payer actor ct.customer tokens and stochasticity.

ct.money-transfer.agent The most relevant property of the x-schema for

payment ct.money this paper is its well-specified execution semantics: payee ct.vendor a transition is enabled when all its input places are Figure 8: The Buy, Sell and Pay schemas. marked, such that it can fire by moving tokens from input to output places. The active execution seman- Other schemas associated with the CT schema tics serves as the engine of context-sensitive infer- lend themselves to similar analyses, though they ence in the simulation-based model of language un- draw on additional schemas not defined here. For derstanding mentioned earlier. example, the Spend schema evokes a schema for re- The ECG formalism is designed to allow con- source consumption (as in (Hudson, 2002)); Charge straints on x-schema simulation to be expressed. involves the vendor’s communication of the price to In particular, the Event schema in Figure 4 has the customer as a prequisite to the overall exchange roles that refer to event phases; these correspond of goods and money. In general, the CT schema to x-schema places and transitions. Other schema explicitly specifies the internal event structure of a roles specify x-schema parameters, which allow x- commercial transaction but remains noncommittal schemas to give rise to different execution traces about which of its participants is seen as active. This through the network with different parameters. flexibility in representation allows other schemas to The Commercial-Transaction schema has been im- effect the bindings that make appropriate commit- plemented in the KarmaSim x-schema simulation ments on an individual basis. environment (Narayanan, 1997); Figure 9 shows 5 Simulation semantics part of the network. The phase roles from the schemas in Section 3 have been mapped onto the The structured event formalism we have described fine-grained temporal structure of each event, corre- allows us to translate FrameNet descriptions into sponding to the various control nodes in the network a representation suitable for simulative inference. (ready, ongoing, finish, done, etc.); the transition phase Central to the representation is an event model referenced in the schemas includes start, ongoing and

Figure 9: KarmaSIM simulation of the Commercial-Transaction schema. The highlighted execution is associated with the Pay schema, corresponding to the money-transfer event.

finish. As shown, execution of the overall CT schema is more challenging, and will require an account of comprises the execution of two subsidiary events, linguistic focus. Such an account remains a topic the goods-transfer and the money-transfer. These need of ongoing research; a preliminary suggestion is to not be synchronized, but both must complete for allow simulation of different parts of the event at the overall commercial transaction to complete (en- varying degrees of detail. For example, the simula- forced by the arcs from ongoing(money-transfer) and tion for Buy may execute the x-schemas in which the ongoing(goods-transfer) to finish(transfers)). Buyer interacts with the Goods – such as the goods- The highlighted money-transfer portion of the net- transfer and its resulting possession (abbreviated as work corresponds to a simulation of the Pay schema. has(Chuck, car) in Figure 9) – at the default granu- The token in ongoing(ct) shows that there is an ongo- larity, while other x-schemas are collapsed into less ing transaction, but the finish(transfers) transition is detailed simulations. not enabled. Technically, the done(ct) place is not Although a detailed treatment of this topic is be- reachable (absent other information), since the sim- yond the scope of this paper, these proposals illus- ulation of Pay does not provide direct evidence for trate how simulation semantics can offer elegant so- the occurrence of a goods-transfer.8 In contrast, both lutions to classic representational problems, or at Buy and Sell involve simulating the entire transac- least facilitate the articulation of factors affecting tion, include both transfers as well as the done(ct) language understanding. node. (Figure 9 can be considered an expansion of the CT schema’s transition phase.) 6 Discussion and conclusions What about the perspectival difference between Frame semantics in general and FrameNet in par- Buy and Sell? The simplest simulative counterpart ticular show considerable promise for use in deep of perspective is the specification of differing actor semantic analysis. FrameNet frames are intended to participants. The actor is defined as supplying tokens needed for simulation (not shown in the fig- capture crucial generalizations not available in other ure), which could be interpreted as providing the lexical resources. WordNet (Fellebaum, 1998), for energy, initiative or control for the event. example, includes only simple taxonomic relations (buy and sell are listed as hyponyms of get and give, Capturing the foregrounding effect of perspective respectively, and as antonyms of each other). The 8Contextual or background knowledge could provide evi- PropBank project (Kingsbury and Palmer, 2002) dence for the other transfer or allow it to be inferred by default. is, like FrameNet, geared toward the creation of a

7 semantically annotated corpus (by adding general standing. Technical Report TR-02-004, International Com- logical predicates to the Penn Treebank), though puter Science Institute. without any common background frame structures Nancy Chang, Daniel Gildea, and Srini Narayanan. 1998. A across lexical items. dynamic model of aspectual composition. In Proceedings of the Twentieth Annual Meeting of the Cognitive Science While frames and FE tags are meaningful to hu- Conference, Madison, Wisconsin. man interpreters, they are not yet suitable for use in NLU. In this paper we have shown how FrameNet Christianne Fellebaum, editor. 1998. WordNet: An Electronic Database. MIT Press. tags can be precisely defined in terms of structured event representations, which can support parameter- Charles J. Fillmore and Collin F. Baker. 2001. Frame semantics for text understanding. In Proceedings of WordNet and ize simulations that license active inferences. The Other Lexical Resources Workshop, Pittsburgh. NAACL. formalism appears expressive enough for the COM- Charles J. Fillmore, Charles Wooters, and Collin Baker. 2001. MERCE frame and its associated perspectival ef- Building a large lexical databank which provides deep se- fects, and we believe the methods we have used will mantics. In Proceedings of the Pacific Asian Conference on scale well for other representational problems. Language, Information and Computation, Hong Kong. Work under way suggests that our schemas, to- Charles J. Fillmore. 1985. Frames and the semantics of under- gether with formalisms developed for linguistic standing. Quaderni di Semantica, IV(2). constructions, can be extended to account for some Jean Mark Gawron. 2002. Frames, modifiers, and argument of the linguistic patterns associated with commer- structure. Manuscript, San Diego State University. cial transactions. For example, a countertheme argu- Daniel Gildea and Daniel Jurafsky. 2000. Automatic labeling ment could be added to each schema in Figure 8 and of semantic roles. In Proceedings of the 38th Annual Meet- bound to the Payment for Buy and Sell and the Goods ing of the ACL, Hong Kong, October. Pay for . A construction associating for-PPs with this Richard Hudson. 2002. Buying and selling in Word Grammar. role could have variable interpretation (relative to In press. the overall CT) for the relevant verbs. Related work Paul Kingsbury and Martha Palmer. 2002. From Treebank to would show how the model could address more PropBank. Submitted to the 3rd International Conference challenging perspective-related phenomena, includ- on Language Resources and Evaluation (LREC-2002). ing reference resolution (e.g., the differing interpre- Tadao Murata. 1989. Petri nets: Properties, analysis, and ap- tation of He in Chuck bought a car from Jerry. He plications. In Proc. IEEE-89, volume 77, pages 541–576. got a 10% discount/?commission) and word sense Srini Narayanan. 1997. Knowledge-based Action Represen- disambiguation (e.g., whether new in Chuck bought tations for Metaphor and Aspect (KARMA). Ph.D. thesis, a new car from Jerry refers to a car that has never University of California at Berkeley. been owned before or to one that has not previously Srini Narayanan. 1999a. Moving right along: A computational been owned by Chuck). model of metaphoric reasoning about events. In Proc. Six- Future work involves extending the representa- teenth National Conference of Artificial Intelligence (AAAI- 99). AAAI Press, Menlo Park. tion to cover a broader subset of the FrameNet database and automating the process of mapping Srini Narayanan. 1999b. Reasoning about actions in narrative understanding. In Proc. Sixteenth International Joint Con- frame definitions to simulation parameterizations. ference on Artificial Intelligence (IJCAI-99). Morgan Kauf- The resulting representations should be useful for a mann Press. variety of NLP applications, including question an- Miriam R.L. Petruck. 1996. Frame semantics. In J. Ver- swering and information extraction. schueren, J. Ostman,¨ J. Blommaert, and C. Bulcaen, editors, Handbook of Pragmatics. John Benjamins, Philadelphia. References Carl Pollard and Ivan A. Sag. 1994. Head-Driven Phrase Structure Grammar. University of Chicago Press, Chicago. Collin F. Baker, Charles J. Fillmore, and John B. Lowe. 1998. The Berkeley FrameNet Project. In Proceedings of Robert D. Van Valin. 1993. A synopsis of role and refer- COLING-ACL, Montreal, Canada. ence grammar. In Robert D. Van Valin, editor, Advances in Role and Reference Grammar, pages 1–166. John Ben- jamins Publishing Company, Amsterdam. Benjamin K. Bergen and Nancy C. Chang. 2002. Embodied Construction Grammar in simulation-based language under-