Triple

T9749171
Position Surface form Disambiguated ID Type / Status
Subject Indre E236394 entity
Predicate contains P35 FINISHED
Object La Châtre E848617 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 Châtre | Statement: [Indre, contains, La Châtre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Châtre
Context triple: [Indre, contains, La Châtre]
  • A. La Châtre chosen
    La Châtre is a small historic town in central France known for its picturesque medieval streets and its association with the writer George Sand.
  • B. Châtellerault
    Châtellerault is a historic town in western France, known for its former royal arms factory and its role as an important industrial and transport hub in the Vienne department.
  • C. Cholet
    Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
  • D. Châteauroux
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f6a2f8c8190a6f6af6587ee90b8 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6525a4af08190bcd8455e95a2f3ae completed April 8, 2026, 1:04 p.m.
Created at: March 30, 2026, 8:23 p.m.