A Robust Semantic Frame Parsing Pipeline on a New Complex Twitter Dataset
Most recent semantic frame parsing systems for spoken language understanding (SLU) are designed based on recurrent neural networks. These systems display decent performance on benchmark SLU datasets such as ATIS or SNIPS, which contain short utterances with relatively simple patterns. However, the current semantic frame parsing models lack a mechanism to handle out-of-distribution (\emph{OOD}) patterns and out-of-vocabulary (\emph{OOV}) tokens. In this paper, we introduce a robust semantic frame parsing pipeline that can handle both \emph{OOD} patterns and \emph{OOV} tokens in conjunction with a new complex Twitter dataset that contains long tweets with more \emph{OOD} patterns and \emph{OOV} tokens. The new pipeline demonstrates much better results in comparison to state-of-the-art baseline SLU models on both the SNIPS dataset and the new Twitter dataset (Our new Twitter dataset can be downloaded from https://1drv.ms/u/s!AroHb-W6_OAlavK4begsDsMALfE?e=c8f2XX ). Finally, we also build an E2E application to demo the feasibility of our algorithm and show why it is useful in real application.
Code (0)
등록된 구현이 없습니다.
Tasks
Semantic Frame ParsingSpoken Language UnderstandingSimilar Papers 제목 키워드 기반
Twitter Universal Dependency Parsing for African-American and Mainstream American English
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. We broaden English dependency parsin…
Dependency ParsingInformation RetrievalLanguage IdentificationPart-Of-Speech Tagging+1Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis
Social media data such as Twitter messages ("tweets") pose a particular challenge to NLP systems because of their short, noisy, and colloquial nature. Tasks such as Named Entity Recognition (NER) and syntactic parsing re…
Dependency Parsingnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+4Towards Transparent Interactive Semantic Parsing via Step-by-Step Correction
Existing studies on semantic parsing focus primarily on mapping a natural-language utterance to a corresponding logical form in one turn. However, because natural language can contain a great deal of ambiguity and variab…
Question AnsweringSemantic ParsingTowards Transparent Interactive Semantic Parsing via Step-by-Step Correction
Existing studies on semantic parsing focus on mapping a natural-language utterance to a logical form (LF) in one turn. However, because natural language may contain ambiguity and variability, this is a difficult challeng…
Question AnsweringSemantic ParsingA Graph-Based Neural Model for End-to-End Frame Semantic Parsing
Frame semantic parsing is a semantic analysis task based on FrameNet which has received great attention recently. The task usually involves three subtasks sequentially: (1) target identification, (2) frame classification…
graph constructionSemantic ParsingSemantic Role Labeling