Triple

T19846573
Position Surface form Disambiguated ID Type / Status
Subject Gare de Tarbes E476875 entity
Predicate locatedIn P40 FINISHED
Object Tarbes NE NERFINISHED

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: Tarbes | Statement: [Gare de Tarbes, locatedIn, Tarbes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarbes
Context triple: [Gare de Tarbes, locatedIn, Tarbes]
  • A. Tarbes chosen
    Tarbes is a historic city in southwestern France, serving as the capital of the Hautes-Pyrénées department at the foot of the Pyrenees.
  • B. Bagnères-de-Bigorre
    Bagnères-de-Bigorre is a spa and ski resort town in the French Pyrenees, known for its thermal baths and mountain tourism.
  • C. Narbonne
    Narbonne is a historic city in southern France known for its Roman heritage, medieval architecture, and former status as an important Mediterranean port.
  • D. Eauze
    Eauze is a historic town in southwestern France, known as a former Roman capital and a center of Armagnac brandy production.
  • E. Saint-Girons
    Saint-Girons is a small town in the Ariège department of southwestern France, situated in the foothills of the Pyrenees.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65809da2c8190bb579ef42513b74d completed April 20, 2026, 4:44 p.m.
Created at: April 10, 2026, 1:51 p.m.