Triple

T21662405
Position Surface form Disambiguated ID Type / Status
Subject Yvonne Loriod E534624 entity
Predicate placeOfBirth P1 FINISHED
Object Houilles NE NERFINISHED

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: Houilles | Statement: [Yvonne Loriod, placeOfBirth, Houilles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Houilles
Context triple: [Yvonne Loriod, placeOfBirth, Houilles]
  • A. Houilles chosen
    Houilles is a suburban commune in north-central France, located in the western outskirts of Paris within the Yvelines department.
  • B. Valenciennes
    Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
  • C. Beauvais
    Beauvais is a historic city in northern France known for its impressive Gothic cathedral and role as the capital of the Oise department.
  • D. Meyriez
    Meyriez is a small municipality in the canton of Fribourg in western Switzerland, situated on the shores of Lake Murten.
  • E. Bressuire
    Bressuire is a historic town in western France known for its medieval castle and role as an administrative center in the Deux-Sèvres department.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c0956e0819093b4794418efe052 completed April 27, 2026, 2 p.m.
Created at: April 16, 2026, 6:36 p.m.