Triple

T8844385
Position Surface form Disambiguated ID Type / Status
Subject Loiret E210466 entity
Predicate hasCity P316 FINISHED
Object Gien E241345 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: Gien | Statement: [Loiret, hasCity, Gien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gien
Context triple: [Loiret, hasCity, Gien]
  • A. Gien chosen
    Gien is a commune in north-central France known for its historic faience (earthenware) production and its location along the Loire River.
  • B. Gerland
    Gerland is a district in the 7th arrondissement of Lyon, France, known for its former stadium, biotechnology and research centers, and mixed residential-industrial character.
  • C. Decize
    Decize is a historic riverside town in central France situated on an island formed by the Loire and Aron rivers.
  • D. Couvin
    Couvin is a municipality in southern Belgium known for its extensive forests, caves, and rural landscapes within the Walloon region.
  • E. Fallières
    Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
  • 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc608a73c88190875409fef79ffc8a completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89ad0a3c8190a2bcf9a106138835 completed April 3, 2026, 9:34 a.m.
Created at: March 30, 2026, 6:48 p.m.