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Let's see how different semantic parsers annotate some NLU datasets (intents+slots)

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MartinoMensio/semantic_parsing_annotations

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Installing

Clone all the submodules: git submodule update --init --recursive

required python2

  • create a venv
  • install required things by using install.sh

Process

  1. download the models for open-sesame and semafor: run get_models.sh
  2. get the corpora: run get_corpora.sh
  3. extract the sentences from the corpora: run text_extract.py
  4. annotate with the prebuilt systems: run annotate.sh
  5. group the annotations on the same sentences: run aligner.py
  6. extract the TSV files for easier comparison: run to_tabular.py

TODOs

automate the framenet source files download?? need:

  • FrameNet: data/fndata-1.7/luIndex.xml
  • preprocessed conll: data/neural/fn1.7/fn1.7.fulltext.train.syntaxnet.conll
  • embeddings: glove.6B.100d.txt

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Let's see how different semantic parsers annotate some NLU datasets (intents+slots)

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