Triple

T9093218
Position Surface form Disambiguated ID Type / Status
Subject Gifhorn E217943 entity
Predicate hasTwinTown P919 FINISHED
Object Hennebont E194476 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: Hennebont | Statement: [Gifhorn, hasTwinTown, Hennebont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hennebont
Context triple: [Gifhorn, hasTwinTown, Hennebont]
  • A. Hennebont chosen
    Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
  • B. Quimperlé
    Quimperlé is a historic town in the Finistère department of Brittany in northwestern France, known for its medieval architecture and picturesque setting at the confluence of three rivers.
  • C. Villeurbannais
    Villeurbannais is the French term for an inhabitant or native of the city of Villeurbanne, located near Lyon in eastern France.
  • D. Châteaubriant
    Châteaubriant is a historic town in western France known for its medieval castle and role as a local administrative and cultural center.
  • E. Auray
    Auray is a historic coastal town in Brittany, northwestern France, known for its picturesque old port of Saint-Goustan and medieval architecture.
  • 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_69ca83d8ab5881909d8fddae363b32b1 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b347d4819085b33d0e20834f47 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d01803b0288190a86b544892d4b6ed completed April 3, 2026, 7:41 p.m.
Created at: March 30, 2026, 7:14 p.m.