1 / 111

Lexical Semantics in American Corpus Annotation Projects

Lexical Semantics in American Corpus Annotation Projects. Lori Levin September 10, 2004 Tutorial at Clairvoyance Corporation. What is Lexical Semantics?. Lexical semantics is about the meanings of words. This tutorial is about the meanings of verbs and their arguments:

nrandall
Download Presentation

Lexical Semantics in American Corpus Annotation Projects

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Lexical Semantics in American Corpus Annotation Projects Lori Levin September 10, 2004 Tutorial at Clairvoyance Corporation

  2. What is Lexical Semantics? • Lexical semantics is about the meanings of words. • This tutorial is about the meanings of verbs and their arguments: • Sam opened the door with a key. • They key opened the door. • The door was opened by Sam with a key. • The door opened (with a key). • Sam bought a book from Sue. • Sue sold a book to Sam.

  3. Types of semantics not covered in this tutorial • Sentence-level meaning • Truth conditions of sentences • This is a picture of a cell phone. (true) • This is a picture of a book. (false) • Compositional semantics • How the meanings of a noun phrase and a verb phrase are combined into the meaning of a sentence. • Quantifier scope. • Everyone here speaks two languages.

  4. Aspects of lexical semantics not covered in this tutorial • Nouns, adjectives, adverbs, and prepositions • Selectional restrictions: • Colorless green ideas sleep furiously. • Chomsky, 1957, Syntactic Structures • Count and mass nouns: • There was water all over the driveway. (mass) • There was dog all over the driveway. (count) • Synonymy, hyponymy, antonymy, etc. • car-automobil • car-vehicle • Hot-cold

  5. Outline • Background • Predicates and Arguments • Valency and subcategories of verb • Optional arguments and adjuncts • Semantic Roles • Three approaches to lexical semantics • A linguistic theory • Lexical Conceptual Structure • A lexicon project • Frame Semantics • A corpus annotation project (also building a lexicon) • PropBank • A multi-lingual semantic corpus annotation project

  6. Predicates and Arguments • Verbs (and sometimes nouns and adjectives) describe events, states, and relations that have a certain number of participants. • The children devoured the spaghetti. • Two participants • The teacherhanded the booktothe student. • Three particpants. • Problems exist. • One participant. • The participants are referred to as arguments of the verb. (Like arguments of a function.)

  7. Valency and Subcategorization • Fillmore and Kay, Lecture Notes, Chapter 4: • The children devoured the spaghetti. • *The children devoured. • *The children devoured the spaghetti the cheese. • She handed the baby a toy. • *She handed the baby. • *She handed the toy. • Problems exist. • *Problems exist more problems.

  8. Grammaticality • An asterisk (*) indicates that a sentence is ungrammatical. • A large percentage of linguists make these assumptions: • Human languages are like formal languages. • Some sentences are in the set of legal sentences and some are not • A human can act like a machine that accepts legal sentences and rejects illegal sentences.

  9. Valency • The number of participants is called the verb’s valence or valency. • Devour has a valency of two. • Hand has a valency of three. • Exist has a valency of one. • Linguists took this term from chemistry – how many electrons are missing from the outer shell. • The first linguist to use the term was Charles Hockett in the 1950’s.

  10. Subcategorization • Verbs are divided into subcategories that have different valencies. • Here is how the terminology works: • Exist, devour, and hand have different subcategorizations • i.e., They are in different subcategories • Devour subcategorizes for a subject and a direct object. • Devour is subcategorized for a subject and a direct object. • Devour takes two arguments, a subject and a direct object (or an agent and a patient).

  11. Arguments are not always Noun Phrases • The italicized phrases are also arguments: • He looked very pale. • Adjective Phrase • The solution turned red. • Adjective Phrase • I want to go. • Verb Phrase • He started singing a song. • Verb Phrase • We drove to New York. • Prepositional Phrase

  12. Optional and Obligatory Arguments • The direct object of eat is optional: • The children ate. • The children ate cake. • The direct object of devour is not optional: • *The children devoured. • The children devoured the cake.

  13. Optional Arguments • The dog ran. • The dog ran from the houseto the creekthrough the gardenalong the path.

  14. Optional vs. Invisible Arguments a. What happened to the cake? b. The children ate. b’. The children ate it. In English, Sentences b and b’ do not mean the same thing in this context. Compare to Japanese and Chinese.

  15. Adjuncts • Locations, times, manners, and other things that can go with almost any sentences are called adjuncts. • The children ate the cake quicklyat 2:00in the kitchen.

  16. How to tell arguments from adjuncts • There are some general guidelines that are not always conclusive. • Adjuncts are always optional. • but some arguments are optional too • Repeatability: • The children devoured the cake at 2:00on Monday. • Two temporal adjuncts • The children devoured the cake in Pittsburghin a restaurant. • Two locative adjuncts • *The children devoured the cakethe dessert. • arguments are not repeatable

  17. Semantic Roles: Motivation • The verb open appears in different subcategorization patterns: • Sam opened the door with a key. • The key opened the door. • The door was opened by Sam with a key. • Sam’s opening of the door with a key • How can we represent the meanings of these sentences in a way that shows that they are related?

  18. These sentences do not have the same meaning even though they have the same verb: Sam interviewed Sue. Sue interviewed Sam. Semantic Roles: Motivation

  19. Semantic Roles: Motivation These sentences mean roughly the same thing even though they use different verbs: • Sam bought a toy from Sue. • Sue sold a toy to Sam.

  20. Semantic Roles: Motivation • The way to express riding a vehicle to a location is different in different languages: • Sam took a bus to school. • Sam ascended to the bus and went to school. (Hebrew) • Sam riding on the bus, went to school. (Japanese) • Sam sat on the bus, went to school. (Chinese) • Sam went to school by bus. • Sam went to school by taking a bus.

  21. Semantic role names in a meaning representation • Sam opened the door with a key. • The key opened the door. • The door was opened by Sam with a key. • Sam’s opening of the door with a key • Open • Agent: Sam • Patient: door • Instrument: key

  22. These sentences do not have the same meaning: Sam interviewed Sue. Sue interviewed Sam. Interview Agent: Sam Patient: Sue Interview Agent: Sue Patient: Sam Semantic Roles Names in a Meaning Representation

  23. Examples of Semantic Roles • Agent: an agent acts volitionally or intentionally • The students worked. • Sue baked a cake.

  24. Examples of Semantic Roles • Experiencer and Perceived: • An experiencer is an animate being that perceives something, cognizes about something, or or experiences an emotion. • The perceived is the thing that the experiencer perceives or the thing that caused the emotional response. • The students like linguistics. • (emoter and perceived) • The students saw a linguist. • (perceiver and perceived) • Linguistics frightens the students. • (emoter and perceived) • The students thought about linguistics. • (cognizer and perceived)

  25. Examples of Semantic Roles • Patient: A patient is affected by an action. • Sam kicked the ball. • Sue cut the cake. • Beneficiary: A beneficiary benefits from an event • Sue baked a cake for Sam. • Sue baked Sam a cake. • Malefactive: Someone is affected adversely by an event. • My dog died on me. • Instrument: • The boy opened the door with a key. • The key opened the door. • Location: • The clock stands on the shelf. • I put the book on the shelf.

  26. Three approaches to semantic roles in meaning representations • Ray Jackendoff (1972, 1990) Linguistic Theory • Lexical Conceptual Structure • The Motion/Location Metaphor • Semantic Roles • Charles Fillmore, FrameNet Project Lexicon • Frame-semantics • Martha Palmer, PropBank Project Corpus Annotation • Predicate-specific role names: • Proto-grammatical relations

  27. Ray Jackendoff • Semantic Interpretation in Generative Grammar, MIT Press, 1972 • Semantic Structures, MIT Press, 1990. • Theory of human cognition • Used by many computational linguists

  28. Lexical Conceptual Structure • Primitives: • GO, BE, STAY, CAUSE, and several more • TO, FROM, AWAY, TOWARD, VIA, and several more • Types of entities: • Event, State, Thing, Place, Path • Other tiers of representation are added in order to capture nuances of meaning and grammar: • Cause and affectedness • Manner • Actor and undergoer (see discussion of PropBank)

  29. Example of Lexical Conceptual Structure Sam threw the ball across the room. [event CAUSE [thing SAM] [event GO [thing BALL] [path TO [place AT [thingother-side-of-room]]]]]

  30. Lexical Conceptual Structure and Semantic Role Names Sam threw the ball across the room. [event CAUSE [thing SAM] agent [event GO [thing BALL] theme [path TO [place AT [thingother-side-of-room]]]]] goal

  31. The Motion/Location Metaphor • J. S. Gruber, Studies in Lexical Relations, MIT Dissertation, 1965. • Agent: causes, manipulates, affects • Theme: changes location, is located somewhere, or exists • Source: the starting point of the motion • Goal: the ending point of the motion • Path: the path of the motion

  32. Examples of Location and Directed Motion • Many problems still exist. • The clock sits on the shelf. • The ball rolled from the door to the window along the wall. • Same walked from his house to town along the river. • Sue rolled across the room. • The car turned into the driveway.

  33. Being in a state or changing state • The car is red. • The ice cream melted. • The glass broke. • Sam broke the glass. • The paper turned from red to green. • The fairy godmother turned the pumpkin into a coach.

  34. Having or Changing possession • The teacher gave books to the students. • The teacher gave the students books. • The students have books.

  35. Exchange of Information • The teacher told a story to the students. • The teacher told the students a story.

  36. Extent • The road extends/runs along the river from the school to the mall. • The string reaches the wall. • The string reaches across the room to the wall.

  37. Strong points of LCS and the Motion/Location Metaphor • Sam manipulates a key, having an effect on the door, causing it to go from the state of being closed to the state of being open. • Sam opened the door with a key. • The key opened the door. • The door was opened by Sam with a key. • Sam’s opening of the door with a key

  38. Strong points of LCS and the Motion/Location Metaphor • A toy goes from Sue to Sam. Some money goes from Sam to Sue. • Differences in the causation tier. • Sam bought a toy from Sue. • Sue sold a toy to Sam.

  39. Strong points of LCS and the Motion/Location Metaphor • Supports some inferences: • If X goes from A to B, then X is no longer at A. • If X is created (begins to BE) during event Y, then X doesn’t exist until Y is finished.

  40. Strong or weak point? • LCS wasn’t designed with this kind of thing in mind, but it could be made to work. • Sam took a bus to school. • Sam ascended to the bus and went to school. (Hebrew) • Sam riding on the bus, went to school. (Japanese) • Sam sat on the bus, went to school. (Chinese) • Sam went to school by bus. • Sam went to school by taking a bus.

  41. Problem with Thematic Roles and the Motion/Location Metaphor • It is not clear how to apply the metaphor to many verbs (Fillmore and Kay, Lecture Notes, pages 4-22) • He risked death. • We resisted the enemy. • She resembles her mother.

  42. LCS Resources • Bonnie Dorr, University of Maryland • http://www.umiacs.umd.edu/~bonnie/LCS_Database_Documentation.html • LCS Lexicon for English • English word senses are mapped to WordNet • Handcrafted lexical entries for around 4000 verbs • Automatically produced entries may be available for a full-sized lexicon • LCS Dictionaries for other languages may be available • May be handcrafted or produced partially automatically

  43. Problem with Thematic Roles and the Motion/Location Metaphor • It is not clear how to apply the metaphor to many verbs (Fillmore and Kay, Lecture Notes, pages 4-22) • He risked death. • We resisted the enemy. • She resembles her mother.

  44. Charles Fillmore, Collin Baker, and othersFrameNet Project • http://www.icsi.berkeley.edu/~framenet/ • Frame semantics • Frames are networked using several relations • Based on corpus analysis • Lexical entries for around 7500 English verbs • Other FrameNet projects in • Spanish • Japanese

  45. Advantage of Frame Semantics • FrameNet was designed to capture the similarities in sentences like these. • Ride-vehicle frameSam took a bus to school. • Sam ascended onto the bus and went to school. (Hebrew) • Sam riding on the bus, went to school. (Japanese) • Sam sat on the bus, went to school. (Chinese) • Sam went to school by bus. • Sam went to school by taking a bus.

  46. Frame Semantics compared to the Motion/Location Metaphor • Frame Semantics has • Many primitives • Many semantic roles

  47. FrameNet strong and weak points • FrameNet is still under development and may change frequently. • Versions are clearly identified. • Lexical entries are very carefully hand crafted.

  48. Martha Palmer and othersThe PropBank Project • http://www.cis.upenn.edu/~ace/ • Annotate the Penn TreeBank with predicate-argument information • Corpus can be used for automatic learning of the surface realization of each argument

  49. PropBank and FrameNet: Close ties • PropBank lexical entries are linked to FrameNet entries. • There are more PropBank entries than FrameNet entries • This paper contains some comparisons of PropBank and Framenet • http://www.cis.upenn.edu/~dgildea/gildea-acl02.pdf • See also VerbNet • http://www.cis.upenn.edu/group/verbnet/

  50. Proto-roles and verb-specific roles • http://www.cis.upenn.edu/~dgildea/Verbs/ • Abandon • Arg0:abandoner • Arg1:thing abandoned, left behind • Arg2:attribute of arg1

More Related