Aaron Steven White

4 paper cards in Mova's library · 2016–2020

Aaron Steven White wrote 4 of the papers Mova reads, in 2016–2020, most of them on Coreference resolution, Universal Dependencies, Semantic role labeling; often with Benjamin Van Durme, Rachel Rudinger, Adam Poliak.

The profile is the library's match of the name; two people with one name are not always told apart.

Ideas Mova took (3)

From the ideas ledger: an idea tried, kept or queued, or measured with no gain, and what it gave.

kept — Give every frame a factuality value, not only neg and cond: happened / did not happen / not asserted (wanted, planned, hoped, asked, ordered) / uncertain (modal, hedge). (Neural Models of Factuality · implication signatures (51 verbs, prag/data/signatures.tsv) set neg/irrealis on «to» complements top-down; courses 7672/2199→7704/2206 with I2 (35db4e3f7))
kept — Let the student remember only factual frames as facts and keep the rest as wishes or plans (world/src/knowledge.rs): «The fox wanted to eat the grapes» must not answer «Did the fox eat the grapes?» with yes. (Neural Models of Factuality · the student treats an irrealis mismatch as NegDisagree; reader alone 7677/2201, with the student 7704/2206 (35db4e3f7))
kept — A realis flag on every frame: did the event happen according to the text? Mova has neg and cond; add «not realised» for the complement of want/plan/try/hope/refuse/promise, for future and modal frames, and for imperatives, so the student does not answer «Did… (Universal Decompositional Semantics on Universal… · realis flag for complements of want/plan/try… and «if» clauses kept (35db4e3f7); modals (will/would/might/may/shall/should) as irrealis dropped: −38 tests, −2…)

Temporal Reasoning in Natural Language Inference (2020)
The paper turns four temporal datasets (TempEval3, TimeBank-Dense, RED and UDS-Time) into NLI pairs about two kinds of temporal reasoning: event order and event duration.
Neural Models of Factuality (2018) 2 ideas kept
Event factuality asks, for each event-denoting predicate, whether the event happened according to the author, on a scale from −3 (certainly not) to +3 (certainly did).
Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework (2017)
The paper turns existing semantic annotations into textual-inference (RTE) pairs with templates. Three resources are recast: semantic proto-roles (SPR, about 155k pairs), FrameNet paraphrases (FN+, about 155k) and definite pronoun resolution (DPR, about 3.7k). Each pair is labelled entailed or not from the original…
Universal Decompositional Semantics on Universal Dependencies (2016) 1 idea kept
The Decomp project adds semantic annotation on top of UD treebanks by asking ordinary speakers simple, decomposed questions with Likert-scale answers instead of asking for labels like Agent.