Triple

T9394341
Position Surface form Disambiguated ID Type / Status
Subject Sister Aloysius Beauvier E226105 entity
Predicate givenName P17 FINISHED
Object Aloysius E175595 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Aloysius | Statement: [Sister Aloysius Beauvier, givenName, Aloysius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aloysius
Context triple: [Sister Aloysius Beauvier, givenName, Aloysius]
  • A. Aloysius chosen
    Aloysius is a masculine given name of Latinized form, historically borne by several saints and used in various European languages.
  • B. Ignazio
    Ignazio is an Italian given name, cognate to Ignacy and typically associated with the Latin-rooted names Ignatius and Ignacio.
  • C. Brother Felix
    Brother Felix is a religious honorific or title used to refer respectfully to a man named Felix, typically within a Christian or monastic context.
  • D. Benedetto
    Benedetto is the Italian form of the given name Benedict, traditionally associated with blessings and several notable religious and historical figures.
  • E. Brother Theodore
    Brother Theodore was a German-American monologist and actor known for his darkly comedic, existential rants and cult appearances on late-night television and in offbeat films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca842f7e3481908bf5bcf52e032dbd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd511150008190be04142e477e8bf1 completed April 1, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1010ffcd4819088edafbdb43c2c00 completed April 4, 2026, 12:16 p.m.
Created at: March 30, 2026, 7:45 p.m.