Triple

T16019609
Position Surface form Disambiguated ID Type / Status
Subject Cergy-Pontoise urban area E388564 entity
Predicate containsCommune P15149 FINISHED
Object Maurecourt E1010965 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: Maurecourt | Statement: [Cergy-Pontoise urban area, containsCommune, Maurecourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maurecourt
Context triple: [Cergy-Pontoise urban area, containsCommune, Maurecourt]
  • A. Maurecourt chosen
    Maurecourt is a small suburban commune in the Yvelines department of north-central France, located in the western outskirts of the Paris metropolitan area.
  • B. Rachecourt
    Rachecourt is a village in the municipality of Aubange in the province of Luxembourg, Belgium.
  • C. Morlaincourt
    Morlaincourt is a small commune in northeastern France, likely known locally for its rural character and proximity to the Yonne river’s headwaters.
  • D. Breteuil
    Breteuil is a commune in northern France that serves as a local administrative and service hub for its surrounding rural area.
  • E. Escoutoux
    Escoutoux is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183222e4c81909a3ab51446b671bd completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00179fc28481909e1c46af343676ff completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 4:55 a.m.