Lucas Champollion

Fine (J Philos Logic 46(6):625–674, 2017) develops a unilateral and a bilateral truthmaker semantics for propositional logic. The unilateral approach trades off the primitive exact falsification relation of the bilateral approach for a primitive exclusion relation between states, thereby raising the question if exclusion serves any purpose other than to avoid exact falsification. We argue that exclusion is motivated independently of its use in avoiding exact falsification, namely as a foundation for the reconstruction of modal notions such as possibility and necessity. This reconstruction in turn motivates what we call _emergent exclusion_: an atomic state can exclude a sum of atomic states collectively without excluding any of these atomic states individually. Emergent exclusion is banned in Fine (2017a) in order to maintain exact equivalence in de Morgan’s law \(\lnot (P \wedge Q) \Leftrightarrow \lnot P \vee \lnot Q\) ; we argue that the two sides of this law are not exactly equivalent and discuss a variety of state spaces that feature emergent exclusion. This paper aims to be accessible to linguists without prior exposure to truthmaker semantics. We highlight points of contact with natural language semantics, such as event semantics and algebraic semantics of plurals and conjunction.

We introduce LTAG-spinal, a novel variant of traditional Lexicalized Tree Adjoining Grammar (LTAG) with desirable linguistic, computational and statistical properties. Unlike in traditional LTAG, subcategorization frames and the argument-adjunct distinction are left underspecified in LTAG-spinal. LTAG-spinal with adjunction constraints is weakly equivalent to LTAG. The LTAG-spinal formalism is used to extract an LTAG-spinal Treebank from the Penn Treebank with Propbank annotation. Based on Propbank annotation, predicate coordination and LTAG adjunction structures are successfully extracted. The LTAG-spinal Treebank makes explicit semantic relations that are implicit or absent from the original PTB. LTAG-spinal provides a very desirable resource for statistical LTAG parsing, incremental parsing, dependency parsing, and semantic parsing. This treebank has been successfully used to train an incremental LTAG-spinal parser and a bidirectional LTAG dependency parser.

Psycholinguistic experiments show that pronouns tend to be resolved differently depending on whether they occur in main or subordinate clauses. If a pronoun in a subordinate clause has more than one potential antecedent in the main clause, then the pronoun tends to refer to the antecedent which has a certain thematic role (depending on the verb and on the subordinating conjunction). In contrast, pronouns in main clauses tend to refer back to the subject of the previous main clause, and this tendency is not affected by any verbs or conjunctions. In natural language processing, these findings have recently led to a proposal that pronoun resolution systems should have a split architecture, i.e. that they should use different mechanisms for pronoun resolution in the two cases. With the help of two parsed and coreference-annotated corpora, this paper estimates the impact of the split-architecture proposal. The findings of this work are as follows: (1) Subject pronouns in authentic texts behave the same way in main and subordinate clauses. (2) The number of sentences in which a split architecture would behave differently than a system that treats both cases the same way is close to zero. Therefore, a separate treatment of resolution within and across units is unlikely to improve the performance of any system. This result casts a doubt on the split-architecture proposal, and more generally on approaches that directly incorporate psycholinguistic results into performance-oriented algorithms for anaphora resolution without assessing the relative importance of the phenomena that underlie them

In this talk, I first systematize the analogies and complete the picture in some corners. Then, I formally relate the three constructions, and I derive their properties from a single operator. Previous analyses were not designed to account for all three constructions at the same time. Accordingly, I not only assess how well they generalize beyond their intended purpose, but I also evaluate them in their own right. Even so, this analysis improves on previous accounts in several ways. Although I will not focus on this in the talk, the analysis of distributive quantification is compatible with more general analyses of cumulative and collective quantification such as Landman (2000).