Triple

T10663998
Position Surface form Disambiguated ID Type / Status
Subject Brive-la-Gaillarde railway station E251302 entity
Predicate connectsTo P845 FINISHED
Object Périgueux E287272 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: Périgueux | Statement: [Brive-la-Gaillarde railway station, connectsTo, Périgueux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Périgueux
Context triple: [Brive-la-Gaillarde railway station, connectsTo, Périgueux]
  • A. Périgueux chosen
    Périgueux is a historic city in southwestern France known for its well-preserved medieval and Renaissance architecture and its rich Gallo-Roman heritage.
  • B. Montluçon
    Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
  • C. Cahors
    Cahors is a historic town in southwestern France renowned for its medieval architecture, including the fortified Valentré Bridge, and its surrounding Malbec wine-producing vineyards.
  • D. Mérignac
    Mérignac is a suburban city in southwestern France, forming part of the Bordeaux metropolitan area and hosting the region’s main international airport.
  • E. Angoulême
    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.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f31db6288190857533213fa9f20d completed April 9, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69d97a9566e08190a92b49ce73963078 completed April 10, 2026, 10:32 p.m.
Created at: April 8, 2026, 9:08 p.m.