Peng Qi

4 paper cards in Mova's library · 2017–2023

Peng Qi wrote 4 of the papers Mova reads, in 2017–2023, most of them on Dependency parsing, Part-of-speech tagging; often with Christopher D. Manning, Christopher Manning, Jason Bolton.

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

Papers

PragmatiCQA: A Dataset for Pragmatic Question Answering in Conversations (2023)
The dataset has 6,873 question-answer pairs in teacher-student conversations about Fandom wiki topics. For each student question the teacher marks literal answer spans, pragmatic spans that answer the follow-up the student is likely to ask, and a paraphrased final answer. Crowdworkers choose topics of mutual interest…
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages (2020)
Stanza is a Python toolkit whose pipeline is neural from raw text to dependencies, for 66 languages. It has a combined tokenizer and sentence splitter, multi-word-token expansion (a frequency lexicon with a sequence-to-sequence model), a POS and feature tagger that conditions XPOS and features on UPOS, a lemmatizer…
Stanford's Graph-based Neural Dependency Parser at the CoNLL 2017 Shared Task (2017)
The Stanford system is a biaffine graph parser: a BiLSTM encoder, separate ReLU layers for the head and dependent roles of arcs and labels, and biaffine scorers for arcs and labels.
Arc-swift: A Novel Transition System for Dependency Parsing (2017)
Transition-based parsers reach a distant attachment only through a sequence of local shifts and reduces, and every step is a place to make an error.