Triple

T11200317
Position Surface form Disambiguated ID Type / Status
Subject Maria Schneider E265021 entity
Predicate familyName P18 FINISHED
Object Gélin
Gélin is a French surname associated with individuals such as the actress Maria Schneider.
 E911672 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: Gélin | Statement: [Maria Schneider, familyName, Gélin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gélin
Context triple: [Maria Schneider, familyName, Gélin]
  • A. Gaume
    Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
  • B. Gleizes
    Gleizes is a French surname most notably associated with Albert Gleizes, a pioneering Cubist painter and theorist.
  • C. Genouillet
    Genouillet is a rare, old white wine grape variety from Central Europe, historically cultivated in France and believed to descend from the ancient Heunisch Weiss lineage.
  • D. Ozanne
    Ozanne is a river in France that serves as a right-bank tributary of the Loir.
  • E. Gouais
    Gouais is an ancient white wine grape variety historically important as a parent of many classic European grape cultivars.
  • 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: Gélin
Triple: [Maria Schneider, familyName, Gélin]
Generated description
Gélin is a French surname associated with individuals such as the actress Maria Schneider.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gélin
Target entity description: Gélin is a French surname associated with individuals such as the actress Maria Schneider.
  • A. Gaume
    Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
  • B. Gleizes
    Gleizes is a French surname most notably associated with Albert Gleizes, a pioneering Cubist painter and theorist.
  • C. Genouillet
    Genouillet is a rare, old white wine grape variety from Central Europe, historically cultivated in France and believed to descend from the ancient Heunisch Weiss lineage.
  • D. Ozanne
    Ozanne is a river in France that serves as a right-bank tributary of the Loir.
  • E. Gouais
    Gouais is an ancient white wine grape variety historically important as a parent of many classic European grape cultivars.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8c1e9f88190b2b42326aba9d778 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4970df7cc81909c3b07ead58513e8 completed April 19, 2026, 8:49 a.m.
NEDg Description generation batch_69e49c09844881908e0d95ba3f239024 completed April 19, 2026, 9:10 a.m.
NED2 Entity disambiguation (via description) batch_69e49e7f8b108190bb69f532adf25809 completed April 19, 2026, 9:21 a.m.
Created at: April 8, 2026, 9:29 p.m.