Update on Soar-based language processing
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1 Update on Soar-based language processing Deryle Lonsdale (and the rest of the BYU NL-Soar Research Group) BYU Linguistics Soar
2 NL-Soar Soar
3 NL-Soar developments Discourse/robotic dialogue ICSLP DoD BRIMS poster Running on Soar Some NLG chunking issues remain Having trouble getting to Fresh start with Soar
4 LG-Soar Soar
5 Overview Link-Grammar Soar Implements syntactic, shallow semantic processing Used for information extraction Components Soar architecture Link Grammar parser Discourse Representation Theory for discourse modeling Discussed in Soar 21, Soar 22 Soar
6 LG-Soar developments Predicate extraction in biomedical texts domain ( NLDB 2006 Two stages: Identify and extract predicate logic forms from medical clinical trial (in)eligibility criteria Match up the information with other data, e.g. patients medical records Result: tool for helping match patients with clinical trials Soar
7 XNL-Soar Soar
8 Our goals Integrate the MP into a cognitive modeling engine Explore language/task-integrations using the MP Test cross-linguistic implementation possibilities with the MP Ultimately, determine whether the MP supports incremental, operator-based processing Soar
9 Our approach Map the syntactic parsing onto operators Integrate external knowledge sources Strengths: We have already done this for NL-Soar The MP has an operator-like feel to it Weaknesses: MP lit sketchy on incremental parsing External knowledge sources incommensurable Our scant knowledge of human performance data Soar
10 Derivational principles Minimalist Principles (Chomsky 1995) Merge Move Hierarchy of Projections (Adger 2003) Nominal: D > (Poss) > n > N Clausal: C > T > (Neg) > (Perf) > (Prog) > (Pass) > v > V Governed by features Strong and weak features NP, VP symmetry including shells Soar
11 Operators and operator types XNL-Soar op types and functions: Lexical access: retrieve & store lexicallyrelated information Merge: construct syntax via MP-specified merge operations Movehead: perform head-to-head movement (via adjunction) HoP: consult hierarchy of projections, return next possible target level Project: create bare-structure maximal projection from lexical item Soar
12 Nominal projections DP s NP Shells Feature checking HoP for nominals Projection of N to NP Bare phrase structure for lexical heads Operators: Project, Merge1, Merge2, Check-Root, and HoP Soar
13 Projection of a DP Soar
14 Verbal projections VP Shells Theta roles & the LCS lexicon ucat grids The HoP for the clause Operators: Merge1, Merge2, Check-root, HoP. Soar
15 Merge 1 st Merge Complement merge based on ucat features 2 nd Merge Specifier merge based on a second ucat feature Soar
16 Projection of a VP: HoP & Merge Soar
17 Move Governed by strong ucat features Two types of movement Head-head movement Creates new structure at the head level Phrasal movement Operators: Copy, Hadjunction Soar
18 External knowledge sources WordNet 2.0 (wordnet.princeton.edu) Lexical semantics: part-of-speech, word senses, subcategorization Inflectional and derivational morphology English LCS lexicon ( Thematic information: θ-grids, θ-roles Used to derive uninterpretable features Triggers syntactic construction Aligned with WordNet information Soar
19 English LCS lexicon data 10.6.a#1#_ag_th,modposs(of)#exonerate#exonerate#exonerate#exonerate+ed# (2.0, _exonerate%2:32:00::) 10.6.a Verbs of Possessional Deprivation: Cheat Verbs/-of WORDS (absolve acquit balk bereave bilk bleed burgle cheat cleanse con cull cure defraud denude deplete depopulate deprive despoil disabuse disarm disencumber dispossess divest drain ease exonerate fleece free gull milk mulct pardon plunder purge purify ransack relieve render rid rifle rob sap strip swindle unburden void wean) ((1 "_ag_th,mod-poss()") (1 "_ag_th,mod-poss(from)") (1 "_ag_th,mod-poss(of)")) "He!!+ed the people (of their rights); He!!+ed him of his sins" Soar
20 Similar Work Incremental parsing in general (Phillips 03) Other linguistic theories for incremental parsing GB (Kolb 1991) Dependency grammar (Milward 1994, Ait- Mokhtar et al. 2002) Categorial Grammar (Izuo 2004) Finite-state methods (Ait-Mokhtar & Chanod 1997) Soar
21 Similar Work Minimalist parsing in other frameworks (Stabler 1997, Harkema 2001) Thematic information and parsing (Schlesewsky & Bornkessel 2004) Crosslinguistic considerations in incremental parsing (Schneider 2000) Human studies on ambiguity, reanalysis Eye tracking (Kamide, Altmann, & Haywood 03) ERP (Bornkessel, Schlesewsky, & Friederici 03) Soar
22 Soar
23 Soar
24 Soar
25 Soar
26 Building a full sentence agent> init-soar agent> r 0: ==>S: S1 2: O: O1 (getword) Input a word: exonerated 4: O: O2 (getword) Input a word: defendants 5: O: O3 (project) --> NP 7: O: O5 (hop) 8: O: O8 (merge1) 10: O: O9 (merge2) --> np 12: O: O14 (hadjoin) --> move N 13: O: O13 (hop) 14: O: O16 (merge1) 16: O: O17 (merge2) --> DP 18: O: O21 (merge1) 20: O: O23 (merge2) --> VP 22: O: O27 (hop) 23: O: O30 (merge1) 25: O: O31 (merge2) --> vp 27: O: O36 (hadjoin) --> move V 28: O: O35 (hop) 29: O: O38 (merge1) 31: O: O39 (merge2) --> TP Soar
27 Current status POC for fundamental syntactic structures Basic sentence types (transitives, unergatives, unaccusatives) All functional and lexical projections in syntactic structure Most feature percolation, feature checking Current system: about 60 productions (cf NL-Soar) External knowledge sources: interfaced via lines of Tcl/Perl Soar
28 Issue Find a balance between generation and parsing Most MP descriptions are generative, not recognitional in focus Is it advisable and well motivated to undo or reverse movements? If not, is generate-and-test the right mechanism for parsing input? What are the implications for learning and bootstrapping language capabilities (e.g. parsing in the service of generation)? Soar
29 Future functionality XP adjunction Assigners/receivers set? Wider coverage of complex constructions Ditransitives, resultatives, causatives, etc. More semantics/deeper semantics. Quantifier raising Scopal relationships C-command and other interpretive mechanisms More detailed LCS structures Web-based Minimalist Parser grapher Soar
30 Future applications: cf. NL-Soar Explore human parser robustness, processing of ambiguity, learning Integrate syntax/semantics into discourse/conversation component Bootstrapping: parsing and generation Develop human-agent & agent-agent comm Parameterize XNL-Soar for processing of other languages besides English Model cognition in reading Model real-time language/task integrations Soar
31 Conclusion Coals Performance? MP not fully explored Reconciling disparate lexical resources is nontrivial (WordNet + LCS) Redoing learning in Soar8 Graphing is more complicated Nuggets Better coverage (Engl. & crosslinguistically) New start in Soar8 State-of-the-art syntax Interest: CUNY Sentence Processing, CogSci Soar
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