Triple

T10865201
Position Surface form Disambiguated ID Type / Status
Subject Rennes-le-Château E256508 entity
Predicate near P350 FINISHED
Object Limoux E420878 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: Limoux | Statement: [Rennes-le-Château, near, Limoux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limoux
Context triple: [Rennes-le-Château, near, Limoux]
  • A. Limoux chosen
    Limoux is a small town in southern France known for its sparkling wine Blanquette de Limoux and its long-running carnival traditions.
  • B. Céret
    Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
  • C. Limoux AOC
    Limoux AOC is a renowned French wine appellation in southern Occitanie, best known for its traditional sparkling wines considered among the oldest in the world.
  • D. Camprodon
    Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
  • E. Villefranche-de-Rouergue
    Villefranche-de-Rouergue is a historic bastide town in southern France known for its medieval architecture and picturesque setting on the Aveyron 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7516b2f148190adbacd35fc8c2056 completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7d5359c8190b46a6b817938eb67 completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:20 p.m.