Triple

T16290659
Position Surface form Disambiguated ID Type / Status
Subject Terret Noir E395511 entity
Predicate relatedVariety P37 FINISHED
Object Terret Blanc
Terret Blanc is a traditional French white grape variety from the Languedoc region, historically used in blends for still and sparkling wines.
E1204907 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: Terret Blanc | Statement: [Terret Noir, relatedVariety, Terret Blanc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terret Blanc
Context triple: [Terret Noir, relatedVariety, Terret Blanc]
  • A. Piétrain
    Piétrain is a village in Walloon Brabant, Belgium, best known as the namesake origin of the Piétrain pig breed.
  • B. Piquepoul Noir
    Piquepoul Noir is a rare, traditional red wine grape variety from southern France, known for producing light, fresh, and aromatic wines often used in blends.
  • C. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • D. Terrier-Rouge
    Terrier-Rouge is a commune in northeastern Haiti known for its rural character and agricultural activities within the Nord-Est department.
  • E. Mouton-Duvernet
    Mouton-Duvernet is a Paris Métro station in the 14th arrondissement, serving the Montparnasse area and named after the French general Régis Barthélemy Mouton-Duvernet.
  • 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: Terret Blanc
Triple: [Terret Noir, relatedVariety, Terret Blanc]
Generated description
Terret Blanc is a traditional French white grape variety from the Languedoc region, historically used in blends for still and sparkling wines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Terret Blanc
Target entity description: Terret Blanc is a traditional French white grape variety from the Languedoc region, historically used in blends for still and sparkling wines.
  • A. Piétrain
    Piétrain is a village in Walloon Brabant, Belgium, best known as the namesake origin of the Piétrain pig breed.
  • B. Piquepoul Noir
    Piquepoul Noir is a rare, traditional red wine grape variety from southern France, known for producing light, fresh, and aromatic wines often used in blends.
  • C. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • D. Terrier-Rouge
    Terrier-Rouge is a commune in northeastern Haiti known for its rural character and agricultural activities within the Nord-Est department.
  • E. Mouton-Duvernet
    Mouton-Duvernet is a Paris Métro station in the 14th arrondissement, serving the Montparnasse area and named after the French general Régis Barthélemy Mouton-Duvernet.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2491821d0819086cffdd7551ba85a completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f97895081909f22ded3507afe14 completed May 10, 2026, 6:03 a.m.
NEDg Description generation batch_6a0020c8f904819090bea8655972fa85 completed May 10, 2026, 6:08 a.m.
NED2 Entity disambiguation (via description) batch_6a00213560588190850ab5a66fc43704 completed May 10, 2026, 6:09 a.m.
Created at: April 10, 2026, 5:05 a.m.