TexTa

TexTa is a tagger that extracts contextual information from free text.

Given a free text, the script is able to extract information about 4 categories: activities, emotions, interactions and places. For each of these categories there is a dictionary, which contains a list of sub-categories.

Text given in input is parsed and then matched to the sub-categories by handwritten rules, which take into account syntactic information (lemmas, Parts-Of-Speech, dependency structure, ...).

Requirements

• Requires Python 3.x
• Requires the following Python libraries:
  • spaCy v2.2.3
  • spaCy language model 'en_core_web_sm' v2.2.5
  • re

Installing spaCy and needed models

• Install spaCy via pip or your preferred method (see here for more details)

  pip install -U spacy

• Download language model

  python spacy -m download en_core_web_sm

Input

• text

[choose how to pass the text to the file and how to get the output]

Output

For each category returns a matches list containing:

• a numeric id for the matched sub-category
• a number that states the point in the sentence where the match starts
• a number that states the point in the sentence where the match ends

e.g. "We're playing games" will return this output:

• [(5133706519360878345, 2, 3), (5133706519360878345, 2, 4), (5133706519360878345, 3, 4)]

• 5133706519360878345 is the id for the sub-category 'leisure'

• 2,3 is the span for 'playing'

• 2,4 is the span for 'playing games'

• 3,4 is the span for 'games'

! notice that in the span interval, the first number is included, the second one is NOT included