Grammar Implementation with Lexicalized Tree Adjoining Grammars and Frame Semantics Further linguistic analyses Laura Kallmeyer, Timm Lichte, Rainer Osswald & Simon Petitjean University of Düsseldorf DGfS CL Fall School, September 13, 2017 SFB 991
Outline of today’s course Extraction phenomena in LTAG 1 Generalization and factorization within the elementary trees 2 Tree families LTAG & metagrammar specification LTAG semantics 3 Synchronous TAGs for semantics Unification-based LTAG semantics with predicate logic Unification-based LTAG semantics with frames Summary & outlook 4 Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 2 2
Outline of today’s course Extraction phenomena in LTAG 1 Generalization and factorization within the elementary trees 2 Tree families LTAG & metagrammar specification LTAG semantics 3 Synchronous TAGs for semantics Unification-based LTAG semantics with predicate logic Unification-based LTAG semantics with frames Summary & outlook 4 Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 3 3
Extraction: some examples certain constructions permit an element in one position to fill the grammatical role associated with another position Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 4 4
Extraction: some examples certain constructions permit an element in one position to fill the grammatical role associated with another position the positions can be arbitrarily far apart Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 5 4
Extraction: some examples certain constructions permit an element in one position to fill the grammatical role associated with another position the positions can be arbitrarily far apart filler – gap constructions topicalization wh-movement relative clause Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 6 4
Extraction: some examples certain constructions permit an element in one position to fill the grammatical role associated with another position the positions can be arbitrarily far apart filler – gap constructions topicalization wh-movement relative clause long-distance dependencies subject extraction object extraction preposition stranding AP complement extraction Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 7 4
Topicalization Topicalization Placing a constituent (subject, object, ...) into a sentence-initial position. Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 8 5
Topicalization Topicalization Placing a constituent (subject, object, ...) into a sentence-initial position. (1) a. Adam gave an apple to Eve. (base configuration) b. an apple i , Adam gave _ i to Eve. (object NP) c. Eve i , Adam gave an apple to _ i . (NP from PP) d. To Eve i , Adam gave an apple _ i . (PP) e. *Adam, _ i gave an apple to Eve. (no subject topicalization!) Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 9 5
Topicalization Unbounded dependency The dependency between an extracted constituent and its trace may extend across more clause boundaries . Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 10 6
Topicalization Unbounded dependency The dependency between an extracted constituent and its trace may extend across more clause boundaries . (2) a. The apple i , Adam ate _ i . b. Apples i , Eve knows (that) Adam loves _ i . c. The apple i , Adam believes (that) Eve knows (that) the snake ate _ i . Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 11 6
Wh-constructions Wh-questions wh-questions involve a (possibly long-distance) extraction of a con- stituent as a wh-phrase . Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 12 7
Wh-constructions Wh-questions wh-questions involve a (possibly long-distance) extraction of a con- stituent as a wh-phrase . (3) a. [Who] i _ i ate my apple? b. [What] i did Eve eat _ i ? c. [Which apple] i did Adam say Eve had eaten _ i ? Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 13 7
Wh-constructions Wh-questions wh-questions involve a (possibly long-distance) extraction of a con- stituent as a wh-phrase . (3) a. [Who] i _ i ate my apple? b. [What] i did Eve eat _ i ? c. [Which apple] i did Adam say Eve had eaten _ i ? Subject-auxiliary inversion wh-questions involve subject-auxiliary inversion : The auxiliary verb (‘do’, ‘have’, ‘be’, ...) precedes the subject. Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 14 7
Subject-auxiliary inversion Obligatory subject-auxiliary inversion in direct questions with object extraction: (4) a. What i does Adam eat _ i ? b. *What i Adam does eat _ i ? c. *What i Adam eats _ i ? Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 15 8
Subject-auxiliary inversion Obligatory subject-auxiliary inversion in direct questions with object extraction: (4) a. What i does Adam eat _ i ? b. *What i Adam does eat _ i ? c. *What i Adam eats _ i ? No subject-auxiliary inversion in embedded wh-questions: (5) a. Eve wonders [what i Adam eats _ i ]. b. *Eve wonders [what i does Adam eat _ i ]. Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 16 8
Subject-auxiliary inversion Obligatory subject-auxiliary inversion in direct questions with object extraction: (4) a. What i does Adam eat _ i ? b. *What i Adam does eat _ i ? c. *What i Adam eats _ i ? No subject-auxiliary inversion in embedded wh-questions: (5) a. Eve wonders [what i Adam eats _ i ]. b. *Eve wonders [what i does Adam eat _ i ]. No subject-auxiliary inversion in topicalization: (6) a. *[The apple] i , has Adam eaten _ i . b. [ The apple ] i Adam has eaten _ i . Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 17 8
Extraction: elementary trees subject extraction object extraction preposition stranding Who i _ i ate the apple? What i did Adam eat _ i ? What i does Adam dream of_ i ? S S S NP i ↓ S NP i ↓ S NP i ↓ S NP i VP NP ↓ VP NP ↓ VP ϵ V NP ↓ V NP i V PP ate eat ϵ dream P ⋄ NP i ϵ Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 18 9
Extraction: features Features for extraction , taken from the XTAG grammar (XTAG Research Group 2001) extracted := + | – indicates extraction in the S-node wh := + | – indicates the presence of a wh-pronoun inv := + | – indicates inversion Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 19 10
Extraction: features Features for extraction , taken from the XTAG grammar (XTAG Research Group 2001) extracted := + | – indicates extraction in the S-node wh := + | – indicates the presence of a wh-pronoun inv := + | – indicates inversion Handling: no inversion with topicalization ( Books i , people read _ i . ) no topicalized subject ( *People i , _ i read books. ) no inversion with subject wh-extraction ( Who i _ i read books? ) inversion with object wh-extraction ( What i do people read _ i ? ) Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 20 10
Extraction: elementary trees with features Elementary tree for subject extraction: � � (7) Who i _ i arrived? inv 4 S wh 3 extr + agr 2 inv 4 3 + NP ↓ wh wh 3 S trace 5 inv – agr 2 � � � � NP trace agr 5 2 � � VP V ϵ arrived Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 21 11
Inversion with object extraction in case of object extraction topicalization → no inversion wh-questions → inversion Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 22 12
Inversion with object extraction in case of object extraction topicalization → no inversion wh-questions → inversion ⇒ equation of the wh feature of the extracted NP and the upper inv feature of the lower S node: � � inv 3 S wh 3 extr + � � � � NP ↓ wh inv 3 3 � � S – inv Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 23 12
Analyses (8) Apples, Adam ate. � � inv 3 S wh 3 + extr � � NP ↓ wh 3 inv 3 agr 2 � � S inv – � � � � NP agr 3sg + 1 wh – � � VP NP ↓ agr 1 � � V NP apples � �� � NP agr 3sg + ate ϵ Adam Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 24 13
Analyses Derived tree with top and botom feature structures: � � inv 3 S wh 3 extr + � � wh inv 3 3 � � NP agr 2 wh – S inv – � � agr 3sg + 1 � � apples VP agr 1 � �� � NP agr 3sg + Adam V NP ate ϵ Kallmeyer, Lichte, Osswald & Petitjean (HHU Düsseldorf) 25 14
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