Proceedings of the LFG 02 Conference National Technical - CSLI ...

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LFG02 – Kuhn: Corpus-based Learning in Stochastic OT-LFG with verbs, auxiliaries, complementizers. The grammar was written and applied with Xerox Linguistic Environment (XLE). 5 As an illustration of the broad range of analyses licensed by the underlying grammar, consider the sample structures in (21) for sentence (20). (20) [So So streng] [sind] [auf den strict are on the Gipfeln] [die Sitten und die Gesetze der Eitelkeiten] summits the customs and the rules of vanities (21) a. VP VP VP AP V PP NP So streng sind auf den Gipfeln die Sitten und die Gesetze der Eitelkeiten b. FP F VP AP F PP VP NP So streng sind auf den Gipfeln die Sitten und die Gesetze der Eitelkeiten c. FP F FP F VP V AP V PP NP So streng sind auf den Gipfeln die Sitten und die Gesetze der Eitelkeiten d. FP F FP F VP AP F PP NP So streng sind auf den Gipfeln die Sitten und die Gesetze der Eitelkeiten The OT constraints The constraints were also encoded using XLE (compare Frank et al. (2001)). The core constraints adopted were inspired by OT accounts of clausal 5 For technical reasons, a generation-based application of the grammar was simulated by parsing all permutations of the string. In future experiments, it should be possible to use the XLE generator. 252
LFG02 – Kuhn: Corpus-based Learning in Stochastic OT-LFG syntax (Grimshaw 1997, Sells 2001a); further constraints were added to ensure distinguishability of candidates. A total of about 90 constraints was used—based on X-bar configurations, precedence relations of grammatical functions/NP types (pronominal vs. full), etc. Due to computation-intensive preprocessing routines for the learning data, required after each change in the assumed constraint set, the learning experiments were only performed on small training sets. The reported results are from a specific sequence of experiments based on 195 training sentences. 5.3 Learning schemes The corpus-based learning was performed with the GLA (using a simple Prolog implementation) in generation-based optimization. As discussed in sec. 4, the GLA is an error-based learning algorithm, i.e., at each state, the learner applies its present, hypothetical ranking. If the predicted winner matches the target output, no adjustment is necessary; if a different output is the target, the constraints violated only by the predicted winner have to be promoted, while those violated only by the target output are demoted. As discussed in sec. 5.1, a realistic approach should compute the target winner based on a bidirectional approach. In order to test the feasibility of such an account— within the limits of the assumptions discussed above—three different learning schemes were compared in the experiment: 1. The “fully supervised” scheme: The exact target structure for the training clauses was manually annotated (based on the standard analysis of German clause structure). 2. The “string-as-target” scheme: No manual annotation was made; all candidates with the right word order count as target winners (no interpretive optimization is performed). Only predicted winners with an incorrect surface order count as errors—i.e., constraints violated by any of the target winners (and not the predicted winner) are demoted. 3. The bidirectional optimization (or “bootstrapping”) scheme: The current ranking is used to determine a target winner among parsing alternatives for the observed string. All other candidates (possibly with correct surface order) count as errors. 6 6 For the bidirectional scheme, two variants were compared: one, in which the same effective ranking—i.e., the ranking after addition of noise—was used in generation and parsing; and another one, in which the initial parsing-based optimization was sampled several times (leading to different effective rankings), in order to determine a larger set of target winners. The evaluation showed that both variants lead to a very similar behavior. 253
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Proceedings of the LFG 02 Conferenc
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Table of Contents Asudeh, Ash 1-18
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The Syntax of Preverbal Particles a
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2 The Problem: Five Conflicting Cla
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(10) CP C ′ XP CP XP The outermos
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(18) CP C ′ C ∅ IP CP IP I I
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1-3, unless problematic assumptions
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(4c) *After [IP last year [IP she r
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The adjunction rule (36) does not b
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(8c) chun isteacht duit [CP[CP nuai
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work on non-projecting categories a
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Coordination and Parallelism in Glu
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Traditional Linear Duplication a, a
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(8) fred : fe see : fe ⊸ je ⊸ s
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us add the following additional con
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3.2 A General Semantic Schema for C
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approach also achieves correct resu
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In summary, to show that two deriva
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Extraction possible from initial (p
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5.3.2 Across-the-Board Extraction T
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Asudeh, Ash (in progress). Resumpti
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Montague, Richard (1974). Formal ph
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Abstract VP-chaining in Oriya (an I
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(3) haata dho-i bhaata khaa-i mun s
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Figure 4. Schematic representation
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the medicine is applied. If overtly
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The control equation in (13) establ
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intervening object and thus ‘kept
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Lexicon L(1): khi-aa-ga-laa: V L(2)
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(20) VP -> VP V' α � *α SIT-IND
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CONSTRAINT SYMMETRY IN OPTIMALITY T
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‘Juan hit that dog with a stick
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‘With what did Juan hit the dog?
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The unexpectedly bad candidate is (
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Amharic (Semitic, Ethiopia) is a pr
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31) Wïšša-w bä=Daniel bet atäg
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A functional PP must contain a head
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appear): A less well known example
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appear on the non-recursive side of
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Publications. Smith Stark, Thomas.
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Abstract The development of large c
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subj : spec : det : pred : the head
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could annotate the CFG rules extrac
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strings in the WSJ section of the P
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Annotation coverage is measured in
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Our grammars are extracted from sec
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Penn-II training set is discarded f
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grammatical functions are more akin
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forms to semi-automatically develop
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Predicate Argument Structure. In: P
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Abstract PARTITIVE NOUN PHRASES IN
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possessive partitives in (7) and (8
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Extraction of constituents of dativ
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iológiát [[az egyik-en]NP __ ]NP
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Unlike post-verbal constituent orde
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uncertainty. Adopting this idea, I
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accounts for genitive possessor nou
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(38) Hungarian TOPIC/SCOPE/FOCUS pa
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The rule in (41) shows that the top
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Payne, John and Erika Chisarik. (20
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��
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��
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��
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��
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��
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��
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��
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GETARUN PARSER Rodolfo Delmonte Abs
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vital aid in the actual development
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levels of representations required
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sentence starts with a verb we let
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adjunct_cp negat pro=CLI, {Case=acc
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4. Parsing Strategies and P
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qualified. The following list of pr
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structure rules, after the head has
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subordinators, and to arguments of
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Hobbs J.R., D.E.Appelt, J.Bear, M.T
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SECTION II: ITALIAN TEXTS o La stor
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Mario criticava luigi perché ha ro
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1. Introduction Since the beginning
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. ⎡FOCUS ⎤ ⎢PRED ‘wonder (
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(12) *ng- oingerang a mlarngii a be
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(17) a. Hine ha- simla še kaniti.
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have resumptive pronouns. Under the
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way to license the same f-structure
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(33) a. Robin met the man that/who
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licensed in the normal way by funct
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description of the situation. Borer
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http://cslipublications.stanford.ed
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A (Discourse) Functional Analysis o
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A multi-factorial LFG analysis of a
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(9) CP (↑ SUBJ)= ↓ ↑=↓ NP C
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Word Order Properties SGF coordinat
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4.1 Asymmetric Analyses Heycock and
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(25) (a) S 〈 der Jäger ging in d
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In sum, the Subject Functor Lineari
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first and second conjunct are disti
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In the Glue Semantics approach (see
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In the optimality-based model, mism
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complementiser (COMPL) may be exten
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BULGARIAN WORD ORDER AND THE ROLE O
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Bulgarian word order and the role o
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Page 225 and 226: 1 Introduction This paper deals wit
Page 227 and 228: (4) To nifiko itan raf-to (*apo ton
Page 229 and 230: That is, in example (6) the partici
Page 231 and 232: (22) To spiti fenotan egataleli-men
Page 233 and 234: state denoted by the adjective appe
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Page 237 and 238: In addition, the lexical representa
Page 239 and 240: In this way, we capture the intuiti
Page 241 and 242: (57) To fagito ine magire-meno/*mag
Page 243 and 244: Corpus-based Learning in Stochastic
Page 245 and 246: LFG02 - Kuhn: Corpus-based Learning
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Page 263 and 264: 1. Introduction In this paper I wil
Page 265 and 266: This strategy has been outlined by
Page 267 and 268: The essence of the new approach is
Page 269 and 270: 3.2. Control relations in Hungarian
Page 271 and 272: complements of the postposition ut
Page 273 and 274: offered a more detailed discussion,
Page 275 and 276: lexical form which argument of this
Page 277 and 278: Berkeley. pp. 18. (On-line publicat
Page 279 and 280: 0. Abstract This paper attempts to
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Page 283 and 284: This property of raising to object
Page 285 and 286: (32) ved/fra å svømme by/from to
Page 287 and 288: (45) *Til å sove ser han ut to (PR
Page 289 and 290: (57) Å gjøre det er blitt tenkt p
Page 291 and 292: Second argument: The preposition do
Page 293 and 294: In Lødrup (2002), I show that most
Page 295 and 296: Teleman, Ulf, Staffan Hellberg and
Page 297 and 298: Abstract Majority of Bantu language
Page 299 and 300: No Object Agreement Bresnan and Mch
Page 301 and 302: (7) a. N-ä-ï- `m-lyì-á k-èlyá
Page 303 and 304: epresent 72% of the total of 312 se
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(19) Markedness Subhierarchies a. *
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4.1 Hierarchy of Morphological Feat
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(30) Harmonic Alignment of (28) wit
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topic-anaphoricity (as a bound pron
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the present analysis highlights the
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Grimshaw, Jane. 2001. Economy of st
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CLITICS AND PHRASAL AFFIXATION IN C
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(2) (a) ...wedi eu gweld nhw. ASP C
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(7) IP (↑GF) = ↓ ↑ = ↓ NP I
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(14) (a) Jovan je čitao knjigu. Jo
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The Principle of Morphological Comp
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3.2 Serbian Pronominal Clitics A se
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Example (35) has the c-structure in
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(43) (a) čovek-: N (↑PRED) = ‘
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(52) (a) jučer: N (ADJ↑) (↑PRE
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Case Marking and Subject Extraction
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objects occur in VP or in I (“obj
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Coordinated structures (14) Peter o
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(20) Han hadde de trodd e ville kom
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(28) a. * Peter forventer [I’ [I
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One disadvantage of this approach i
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6.2 Case Assignment and Empty Categ
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Lets us consider the binding condit
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claims that subject extraction is n
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ham: N ( (SUBJ £ ) ¡ ((COMP SUBJ
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[Vikner and Schwartz, 1996] Vikner,
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. Mary-ka ttal-lul sakwa-lul mek-I-
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In (4a), the object of the simple d
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3. Morphological Causatives in Kore
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. Mary-ka ttal-pakkey sakwa-ul an m
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Firstly, objects in MC are asymmetr
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The asymmetries of double accusativ
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Abstract The paper describes a pres
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construction - in good style. • I
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Figure 4: Attributed adjectives (
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Aspects of the syntax of psychologi
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Despite the syntactic differences e
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e. (exists independently of the eve
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(10) Poco a poco, me enfadó que pe
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to (3), we can thematically charact
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we can derive the grammatical funct
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‘This book interests him (John).
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unaccusative verb, while interesar
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Roegiest, E. (1999). Objet direct p
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Abstract The aim of this paper is t
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(6) Pierre lui a fait écrire une l
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dative NPs that the examples (4) to
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verb. In some languages, like Engli
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(15) *J’ai convaincu de lui tél
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VP � V + V + (NP) + (PP) (��
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a number of signs (words or phrases
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��
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DAVIS, A. & P.-J. KOENIG (2000) Lin
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1. Introduction Subsumption and Equ
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an XCOMP attribute whose value is t
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(8) a. S|VP Æ NP* (V’) ( S|VP )
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inconsistency with erzählen. But i
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We revise the fronted S|VP expansio
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5. The interaction between PVPF and
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(28) Ein Aussenseiter versuchte hie
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. * Ein Aussenseiter gewonnen haben
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The use of subsumption addresses fu
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TIGER TRANSFER Utilizing LFG Parses
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is an additional way of ensuring co
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"tiger_4548: Hier herrscht Demokrat
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y a multi-set of OT marks, thereby
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sumably they cannot be fixed in pri
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¢¡¤£¦¥¦§©¨�£¦§�¥
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Macros and Templates The system all
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Ambiguous Predicates A simple examp
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HD−OUT TI−FORM herrscht, TI−M
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(ignoring PP-attachment for the eva
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Kameyama, Megumi, Ryo Ochitani, and
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