Identifying ambiguity in semantic resources

A computer program product for dictionary membership management, the computer program product comprising:

• a computer readable storage medium;
• and
• program code embodied therewith with the computer readable storage medium, the program code executable by a processor to:
• apply natural language processing (NLP) to a textual corpus, including apply seed terms of a dictionary to the textual corpus and identify one or more matching items in the textual corpus;
• characterize linguistic properties of each matching item in the textual corpus, including construct a context pattern from the textual corpus for each of the identified one or more matching items;
• apply each constructed context pattern to the dictionary;
• identify matching content between the seed terms of the dictionary and content of the context pattern;
• quantify the identified matching content, including assess scores for the seed terms, the score for the seed term representative of a quantity of the context patterns matching the seed term;
• identify one or more anomalous terms from the seed terms of the dictionary, the one or more anomalous seed terms having ambiguous behavior as reflected in the quantification;
• and
• selectively remove the identified one or more anomalous seed terms from the dictionary, including to selectively remove at least the anomalous seed term associated with the score corresponding to the highest quantity of matching context patterns.

A method comprising:

• applying natural language processing (NLP) to a textual corpus, including applying seed terms of a dictionary to the textual corpus and identifying one or more matching items in the textual corpus;
• characterizing linguistic properties for each matching item in the textual corpus, including constructing a context pattern from the textual corpus for each of the identified one or more matching items;
• applying each constructed context pattern to the dictionary;
• identifying matching content between the seed terms of the dictionary and content of the constructed context pattern corresponding to the seed terms;
• quantifying the identified matching content, including assessing scores for the seed terms, the score for the seed term representative of a quantity of the context patterns matching the seed term;
• identifying one or more anomalous terms from the seed terms of the dictionary, the one or more anomalous terms having ambiguous behavior as reflected in the quantification;
• and
• selectively removing the identified one or more anomalous seed terms from the dictionary, including selectively removing at least the anomalous seed term associated with the score corresponding to the highest quantity of matching context patterns.