Triple

T3853551
Position Surface form Disambiguated ID Type / Status
Subject Languedoc AOC E85355 entity
Predicate subregionsInclude P9956 FINISHED
Object Cabrières
Cabrières is a French wine-producing area in the Languedoc region, known for its distinctive red and rosé wines made primarily from Mediterranean grape varieties.
 E443383 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: Cabrières | Statement: [Languedoc AOC, subregionsInclude, Cabrières]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cabrières
Context triple: [Languedoc AOC, subregionsInclude, Cabrières]
  • A. 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.
  • B. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • C. Eygues
    Eygues is a river in southeastern France that flows through the Drôme department before joining the larger Rhône basin.
  • D. Draguignan
    Draguignan is a town in southeastern France’s Var department, known as a former prefecture and gateway to the Provence region.
  • E. Largentière
    Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
  • 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: Cabrières
Triple: [Languedoc AOC, subregionsInclude, Cabrières]
Generated description
Cabrières is a French wine-producing area in the Languedoc region, known for its distinctive red and rosé wines made primarily from Mediterranean grape varieties.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cabrières
Target entity description: Cabrières is a French wine-producing area in the Languedoc region, known for its distinctive red and rosé wines made primarily from Mediterranean grape varieties.
  • A. 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.
  • B. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • C. Eygues
    Eygues is a river in southeastern France that flows through the Drôme department before joining the larger Rhône basin.
  • D. Draguignan
    Draguignan is a town in southeastern France’s Var department, known as a former prefecture and gateway to the Provence region.
  • E. Largentière
    Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef90e5f408190abf8353e153d1558 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b63702874881909610763d5a48b09d completed March 15, 2026, 4:35 a.m.
NEDg Description generation batch_69b63823c30c8190af727acae00da9d3 completed March 15, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69b638a398f88190bd0f041e9494aeba completed March 15, 2026, 4:42 a.m.
Created at: March 9, 2026, 3:19 p.m.