posextract 1.2.3

Grammatical information extraction methods designed for the analysis of historical and contemporary textual corpora.

posextract

posextract offers grammatical information extraction methods designed for the analysis of historical and contemporary textual corpora. It traverses the syntactic dependency relations between parts-of-speech and returns sequences of words that share a grammatical relationship. See our article for more. You can also download posextract for pypi with pip.

Usage

• extract_triples to extract subject-verb-object (SVO) and subject-verb-adjective complement (SVA) triples
• extract_adj_noun_pairs to extract adjective-noun pairs
• extract_subj_verb_pairs to extract subject-verb pairs

Required Paramters:

• input can be the name of a csv file or an input string
• output name of the output file

Optional Paramters:

• --data_column specify the column to extract triples from.
• --id_column specify a unique ID field if csv file is given.
• --file-delimiter specify comma, pipe, or tab. Default is comma.
• --post-combine-adj combine triples (adjective predicate with object)
• --add-auxiliary extract future and past tense triples.
• --prep-phrase extract the . Default set to false.
• --no-compound-noun Extract just the subject or object (e.g. "Indian Government" is extracted as just "Government").
• --lemma specify whether to lemmatize parts-of-speech. Default is non-lemmatized.
• --verbose print

Examples

Interactive:

Extract grammatical triples.

from posextract import grammatical_triples

triples = grammatical_triples.extract(['Landlords may exercise oppression.', 'The soldiers were ill.'])

for triple in triples:
    print(triple)

# Output: Landlords exercise oppression, soldiers were ill

Extract grammatical triples using different options from default:

from posextract.util import TripleExtractorOptions

triples = grammatical_triples.extract(sent, TripleExtractorOptions(prep_phrase = True))

Or extract adjectives and the nouns they modify.

from posextract import adj_noun_pairs

adj_noun = adj_noun_pairs.extract()

Or extract subjects and their verbs.

from posextract import subj_verb_pairs

subj_verb = subj_verb_pairs.extract()

Over CLI:

posextract can extract grammatical triples from text:

python -m posextract.extract_triples "Landlords may exercise oppression." output.csv

# Output: Landlords exercise oppression

posextract can extract SVO/SVA relationships separately or it can combine the adjective as part of a SVO triple:

python -m posextract.extract_triples "The soldiers were terminally ill." output.csv --post-combine-adj

# Output: soldiers were terminally, soldiers were ill 

python -m posextract.extract_triples "The soldiers were terminally ill." output.csv --post-combine-adj

# Output: soldiers were terminally ill

If provided a .csv file:

python -m posextract.extract_triples --data_column sentence --id_column sentence_id input.csv output.csv

For More Information...

... see our Wiki:

• About Our Evaluation Data
• About the Syntactic Dependency Parser
• How to Use posextract on Databricks