Triple

T14962913
Position Surface form Disambiguated ID Type / Status
Subject Esme Louise Sutter E373109 entity
Predicate middleName P143 FINISHED
Object Louise E5411 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: Louise | Statement: [Esme Louise Sutter, middleName, Louise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louise
Context triple: [Esme Louise Sutter, middleName, Louise]
  • A. Louise chosen
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • B. Louise
    Louise is an opera by French composer Gustave Charpentier, renowned for its realistic portrayal of Parisian working-class life and its influential role in early 20th-century French opera.
  • C. Georgette
    Georgette is a comic servant character in Molière’s play "L’École des femmes," known for her earthy wit and role in highlighting the play’s social and gender tensions.
  • D. Georgette
    Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
  • E. Émilie
    Émilie is the given first name of the French-born American actress Claudette Colbert, a major Hollywood star of the 1930s and 1940s.
  • 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6d0487c8190b7754af8c5014b37 completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae0652dc8190a90a1c3b07a6ed94 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 2:40 a.m.