Triple

T11287378
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 13 E267231 entity
Predicate passesThrough P225 FINISHED
Object Montrouge E854634 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: Montrouge | Statement: [Paris Métro Line 13, passesThrough, Montrouge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montrouge
Context triple: [Paris Métro Line 13, passesThrough, Montrouge]
  • A. Montrouge chosen
    Montrouge is a suburban commune just south of Paris, France, known for its dense urban character and proximity to the capital.
  • B. Bagnolet
    Bagnolet is a suburban commune in the eastern outskirts of Paris, France, known for its dense urban environment and major transport links including the Gallieni bus terminal.
  • C. Levallois-Perret
    Levallois-Perret is a densely populated suburban commune just northwest of central Paris, known for its residential character and proximity to the capital.
  • D. Fontenay-aux-Roses
    Fontenay-aux-Roses is a suburban commune in the southern outskirts of Paris, France, known for its residential character and historical ties to notable French artists and intellectuals.
  • E. Villetaneuse
    Villetaneuse is a suburban commune in the northern outskirts of Paris, France, known for its residential character and the presence of the Université Paris 13 campus.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e986b0f08190a414749eaa7f1a5d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd32359c54819098349d7d1c1e454f completed May 8, 2026, 12:45 a.m.
Created at: April 8, 2026, 9:32 p.m.