nawaz-kmr/Airline-Travel-Information-System-ATIS-Text-Analysis
In this project, you will learn how to generate a complete semantic parse of utterances. First, you will make a discovery on your dataset to get insights about the dataset analytics. Then, you will learn, to extract entities with two different techniques – with spaCy Matcher and by walking on the dependency tree. Next, you will learn different ways of performing intent recognition by analyzing the sentence structure. Finally, you will put all the information together to generate a semantic parse.
No commits in the last 6 months.
Stars
2
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Nov 05, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/nawaz-kmr/Airline-Travel-Information-System-ATIS-Text-Analysis"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
sz128/slot_filling_and_intent_detection_of_SLU
slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s...
yuanxiaosc/BERT-for-Sequence-Labeling-and-Text-Classification
This is the template code to use BERT for sequence lableing and text classification, in order to...
asappresearch/dialog-intent-induction
Code and data for paper "Dialog Intent Induction with Deep Multi-View Clustering", Hugh Perkins...
dborrelli/chat-intents
Clustering sentence embeddings to extract message intent
hellohaptik/HINT3
This repository contains datasets and code for the paper "HINT3: Raising the bar for Intent...