Triple

T7097126
Position Surface form Disambiguated ID Type / Status
Subject Hôtel de Ville de Clichy E165357 entity
Predicate locatedIn P40 FINISHED
Object Clichy E393898 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: Clichy | Statement: [Hôtel de Ville de Clichy, locatedIn, Clichy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clichy
Context triple: [Hôtel de Ville de Clichy, locatedIn, Clichy]
  • A. Clichy chosen
    Clichy is a suburban commune in the northwestern outskirts of Paris, France, known for its dense urban character and role as a residential and business hub.
  • B. Aubervilliers
    Aubervilliers is a densely populated suburban commune in the northeastern outskirts of Paris, known for its industrial past and cultural diversity.
  • C. Clignancourt
    Clignancourt is a northern Paris neighborhood known for its proximity to Montmartre and its famous flea market at Saint-Ouen.
  • D. Courbevoie
    Courbevoie is a suburban commune in the Hauts-de-Seine department of the Île-de-France region, located just west of central Paris and known for encompassing part of the La Défense business district.
  • E. Asnières-sur-Seine
    Asnières-sur-Seine is a suburban commune in the northwestern outskirts of Paris, France, known for its residential neighborhoods and location along the Seine River.
  • 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_69c6887e8c10819091cee237560d32da completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5561dd08190be6b784754a0c1bc completed March 27, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d05bd623b88190aeecaa70f92e5c3c completed April 4, 2026, 12:31 a.m.
Created at: March 27, 2026, 2:41 p.m.