Triple

T16808711
Position Surface form Disambiguated ID Type / Status
Subject Linda Oubre E408547 entity
Predicate familyName P18 FINISHED
Object Oubre
Oubre is a surname of French origin borne by various individuals, including professionals in fields such as education, sports, and the arts.
E1234894 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: Oubre | Statement: [Linda Oubre, familyName, Oubre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oubre
Context triple: [Linda Oubre, familyName, Oubre]
  • A. Ourique
    Ourique is a rural municipality in Portugal’s Alentejo region, known for its historical links to the legendary Battle of Ourique and its traditional agricultural landscape.
  • B. Thieux
    Thieux is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
  • C. Onnaing
    Onnaing is a commune in northern France known for hosting a major Toyota automobile manufacturing plant.
  • D. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • E. Butre
    Butre is a coastal village in Ghana known for its historic role in European colonial trade and the presence of the former Dutch fort, Fort Batenstein.
  • 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: Oubre
Triple: [Linda Oubre, familyName, Oubre]
Generated description
Oubre is a surname of French origin borne by various individuals, including professionals in fields such as education, sports, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oubre
Target entity description: Oubre is a surname of French origin borne by various individuals, including professionals in fields such as education, sports, and the arts.
  • A. Ourique
    Ourique is a rural municipality in Portugal’s Alentejo region, known for its historical links to the legendary Battle of Ourique and its traditional agricultural landscape.
  • B. Thieux
    Thieux is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
  • C. Onnaing
    Onnaing is a commune in northern France known for hosting a major Toyota automobile manufacturing plant.
  • D. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • E. Butre
    Butre is a coastal village in Ghana known for its historic role in European colonial trade and the presence of the former Dutch fort, Fort Batenstein.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2ceab608190a9c8cd339ddbea0a completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b28f125481909664363904f4c031 completed May 10, 2026, 4:30 p.m.
NEDg Description generation batch_6a00b399786c8190acbd188ab55b1fa0 completed May 10, 2026, 4:34 p.m.
NED2 Entity disambiguation (via description) batch_6a00b466ecd08190b7b5ee54476631ab completed May 10, 2026, 4:37 p.m.
Created at: April 10, 2026, 5:23 a.m.