Triple

T8296608
Position Surface form Disambiguated ID Type / Status
Subject A20 motorway E194234 entity
Predicate passesThrough P225 FINISHED
Object Limoges E49689 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: Limoges | Statement: [A20 motorway, passesThrough, Limoges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limoges
Context triple: [A20 motorway, passesThrough, Limoges]
  • A. Limoges chosen
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • B. Aubusson
    Aubusson is a town in central France renowned for its centuries-old tradition of tapestry and carpet weaving.
  • C. Vichy
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • D. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • E. Rousset
    Rousset is a French town in the Provence-Alpes-Côte d’Azur region known for hosting significant semiconductor and microelectronics facilities, including a major STMicroelectronics design center.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df887148190bddc2609bc885cb4 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd953b5fd881909696eb2647dc5f92 completed April 1, 2026, 9:59 p.m.
Created at: March 30, 2026, 5:53 p.m.