Triple

T4472525
Position Surface form Disambiguated ID Type / Status
Subject Manche E98526 entity
Predicate subprefecture P9697 FINISHED
Object Coutances E319547 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: Coutances | Statement: [Manche, subprefecture, Coutances]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coutances
Context triple: [Manche, subprefecture, Coutances]
  • A. Coutances chosen
    Coutances is a historic town in northwestern France known for its Gothic cathedral and role as an administrative and cultural center in the Manche department of Normandy.
  • B. Angeville
    Angeville is a small commune in the Tarn-et-Garonne department in southern France.
  • C. Senlis
    Senlis is a historic town in northern France known for its medieval architecture and its role in events such as the 14th-century Jacquerie peasant revolt.
  • D. Avranches
    Avranches is a historic town in northwestern France, near Mont-Saint-Michel, known for its medieval heritage and role in the liberation of Normandy during World War II.
  • E. Châteaubriant
    Châteaubriant is a historic town in western France known for its medieval castle and role as a local administrative and cultural center.
  • 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356b832c0819096f76b694277d36e completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b628764bf081909a7a1079d0176c66 completed March 15, 2026, 3:33 a.m.
Created at: March 12, 2026, 11:35 p.m.