Triple

T5876825
Position Surface form Disambiguated ID Type / Status
Subject Château de Tarascon E130645 entity
Predicate locatedNear P294 FINISHED
Object Beaucaire E168753 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: Beaucaire | Statement: [Château de Tarascon, locatedNear, Beaucaire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beaucaire
Context triple: [Château de Tarascon, locatedNear, Beaucaire]
  • A. Beaucaire chosen
    Beaucaire is a historic town in southern France known for its medieval architecture and its location along the Rhône River.
  • B. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
  • C. Ribérac
    Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
  • D. Guéret
    Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
  • E. Anduze
    Anduze is a historic town in southern France, known as a gateway to the Cévennes region and for its traditional pottery and scenic setting along the Gardon 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0362fb6948190bdbb3f1d446d070c completed March 22, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e377e1108190b0820f92eab012c2 completed March 23, 2026, 6:53 a.m.
Created at: March 22, 2026, 3:57 p.m.