Triple

T15308583
Position Surface form Disambiguated ID Type / Status
Subject Le Havre urban area E365969 entity
Predicate hasPart P35 FINISHED
Object Harfleur E902349 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: Harfleur | Statement: [Le Havre urban area, hasPart, Harfleur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harfleur
Context triple: [Le Havre urban area, hasPart, Harfleur]
  • A. Harfleur chosen
    Harfleur is a historic port town in Normandy, northern France, known for its strategic importance during the Hundred Years’ War.
  • B. Fécamp
    Fécamp is a coastal town and former important fishing port in northern France, known for its historic Benedictine Palace and dramatic cliffs along the English Channel.
  • C. Bellême
    Bellême is a historic town in northwestern France’s Normandy region, known for its medieval architecture and picturesque setting on the edge of the Perche forest.
  • D. Falaise
    Falaise is a town in Normandy, France, known for its strategic role in the Second World War, particularly during the closing of the Falaise Pocket in 1944.
  • E. Bayeux
    Bayeux is a municipality in the Brazilian state of Paraíba, located in the northeastern region of the country and forming part of the João Pessoa metropolitan area.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd001b48190bbdd69337efdb907 completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef89feda88190b18f6a03d6e968aa completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.