Triple

T14828984
Position Surface form Disambiguated ID Type / Status
Subject Tramway T3a E348647 entity
Predicate terminus P388 FINISHED
Object Porte de Vincennes E227619 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: Porte de Vincennes | Statement: [Tramway T3a, terminus, Porte de Vincennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porte de Vincennes
Context triple: [Tramway T3a, terminus, Porte de Vincennes]
  • A. Porte de Vincennes chosen
    Porte de Vincennes is a major Parisian intersection and metro station in the 12th arrondissement, serving as a key gateway between central Paris and its eastern suburbs.
  • B. Porte du Soubeyran
    Porte du Soubeyran is a historic medieval city gate and landmark in the town of Marvejols in southern France.
  • C. Porte Molitor
    Porte Molitor is a Paris Métro station in the 16th arrondissement of Paris, France.
  • D. Porte Saint-Denis
    Porte Saint-Denis is a monumental triumphal arch in Paris, built in the 17th century to commemorate the military victories of King Louis XIV.
  • E. Porte de la République
    Porte de la République is a historic city gate in Avignon, France, forming part of the town’s medieval fortifications.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded0737d4c8190a49bf6b013da208c completed April 14, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe38a16fd881909d246d8d1811a673 completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:51 a.m.