no code implementations • IJCNLP 2019 • H, Abram ler, Brendan O{'}Connor
Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface.
no code implementations • WS 2019 • H, Abram ler, Premkumar Ganeshkumar, Brendan O{'}Connor, Mohamed Altantawy
We present a model which responds to such queries by returning one or more short, importance-ranked, natural language descriptions of the relationship between two requested concepts, for display in a visual interface.
no code implementations • WS 2018 • Johnny Wei, Khiem Pham, Brendan O{'}Connor, Brian Dillon
We explore whether such output belongs to a formal and realistic grammar, by employing the English Resource Grammar (ERG), a broad coverage, linguistically precise HPSG-based grammar of English.
1 code implementation • EMNLP 2018 • Katherine Keith, Brendan O{'}Connor
Prevalence estimation is the task of inferring the relative frequency of classes of unlabeled examples in a group{---}for example, the proportion of a document collection with positive sentiment.
no code implementations • ACL 2018 • Su Lin Blodgett, Johnny Wei, Brendan O{'}Connor
Due to the presence of both Twitter-specific conventions and non-standard and dialectal language, Twitter presents a significant parsing challenge to current dependency parsing tools.
no code implementations • NAACL 2018 • H, Abram ler, Brendan O{'}Connor
This work introduces a new problem, relational summarization, in which the goal is to generate a natural language summary of the relationship between two lexical items in a corpus, without reference to a knowledge base.
no code implementations • WS 2017 • Su Lin Blodgett, Johnny Wei, Brendan O{'}Connor
While language identification works well on standard texts, it performs much worse on social media language, in particular dialectal language{---}even for English.