Triple

T9505409
Position Surface form Disambiguated ID Type / Status
Subject Sarthe E229255 entity
Predicate contains P35 FINISHED
Object La Flèche E242466 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: La Flèche | Statement: [Sarthe, contains, La Flèche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Flèche
Context triple: [Sarthe, contains, La Flèche]
  • A. La Flèche chosen
    La Flèche is a historic town in western France known for its royal heritage, educational institutions, and the renowned Zoo de La Flèche.
  • B. Fort-de-France
    Fort-de-France is the largest city and administrative, economic, and cultural center of the French Caribbean island of Martinique.
  • C. Saumur
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • D. Alençon
    Alençon is a historic town in northwestern France renowned for its fine lace-making tradition and architectural heritage.
  • E. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9850fe6c8190a5a96cfae12562c6 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d20cbe7fb88190a945870540d4c973 completed April 5, 2026, 7:18 a.m.
Created at: March 30, 2026, 7:57 p.m.