Triple

T6758452
Position Surface form Disambiguated ID Type / Status
Subject Guy of Lusignan E154524 entity
Predicate region P40 FINISHED
Object Angoulême E235549 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: Angoulême | Statement: [Guy of Lusignan, region, Angoulême]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angoulême
Context triple: [Guy of Lusignan, region, Angoulême]
  • A. Angoulême chosen
    Angoulême is a historic city in southwestern France known for its hilltop old town, medieval ramparts, and status as a major center of the French comics industry.
  • B. Saintes
    Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
  • C. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • D. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • E. Saumur
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • 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_69c6880fd5808190be684854081e27dd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1f90b6c8190b4a17a23aa9ba0fb completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8eee797a881909548186742cf7b66 completed March 29, 2026, 9:20 a.m.
Created at: March 27, 2026, 2:11 p.m.