Triple

T15308609
Position Surface form Disambiguated ID Type / Status
Subject Le Havre urban area E365969 entity
Predicate hasPart P35 FINISHED
Object Bernières
Bernières is a locality that forms part of the greater Le Havre urban area in northern France.
 E1154514 NE FINISHED

How this triple was built (4 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: Bernières | Statement: [Le Havre urban area, hasPart, Bernières]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bernières
Context triple: [Le Havre urban area, hasPart, Bernières]
  • A. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • B. Verrières
    Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
  • C. Bédarieux
    Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
  • D. Eygalières
    Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
  • E. Beaumains
    Beaumains is the nickname given to Sir Gareth, a knight of the Round Table in Arthurian legend known for his humble beginnings and later heroic deeds.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bernières
Triple: [Le Havre urban area, hasPart, Bernières]
Generated description
Bernières is a locality that forms part of the greater Le Havre urban area in northern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bernières
Target entity description: Bernières is a locality that forms part of the greater Le Havre urban area in northern France.
  • A. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • B. Verrières
    Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
  • C. Bédarieux
    Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
  • D. Eygalières
    Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
  • E. Beaumains
    Beaumains is the nickname given to Sir Gareth, a knight of the Round Table in Arthurian legend known for his humble beginnings and later heroic deeds.
  • F. None of above. chosen

Provenance (5 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_69ff133d171c8190918c9624bcdb7451 completed May 9, 2026, 10:58 a.m.
NEDg Description generation batch_69ff142e99e081909d01cac0416f1bde completed May 9, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69ff14c61eb08190ba854b541eb1ce14 completed May 9, 2026, 11:04 a.m.
Created at: April 10, 2026, 3:16 a.m.