Triple

T3462783
Position Surface form Disambiguated ID Type / Status
Subject Hortense Fiquet E73065 entity
Predicate givenName P17 FINISHED
Object Hortense E73065 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: Hortense | Statement: [Hortense Fiquet, givenName, Hortense]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hortense
Context triple: [Hortense Fiquet, givenName, Hortense]
  • A. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • B. Hortense Mancini
    Hortense Mancini was a 17th-century Italian-born noblewoman and famed beauty who became one of the most celebrated Mazarinettes at the French court and later a noted memoirist and salonnière in England.
  • C. Hortense Fiquet chosen
    Hortense Fiquet was a French model best known as the wife and frequent portrait subject of the painter Paul Cézanne.
  • D. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • E. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae867c4819091c76e63e44290b4 completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3612392308190b73dc2c757d02742 completed March 13, 2026, 12:58 a.m.
Created at: March 8, 2026, 3:17 p.m.