Triple

T4298573
Position Surface form Disambiguated ID Type / Status
Subject Hautes-Alpes E99775 entity
Predicate contains P35 FINISHED
Object Vars
Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
E429936 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: Vars | Statement: [Hautes-Alpes, contains, Vars]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vars
Context triple: [Hautes-Alpes, contains, Vars]
  • A. Var
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • B. Var
    Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
  • C. VAR
    VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
  • D. Varig
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • E. Vari
    Vari is a settlement on the Greek island of Syros, known for its coastal location and beaches in the Cyclades.
  • 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: Vars
Triple: [Hautes-Alpes, contains, Vars]
Generated description
Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vars
Target entity description: Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
  • A. Var
    Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
  • B. Var
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • C. VAR
    VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
  • D. Varig
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • E. Vari
    Vari is a settlement on the Greek island of Syros, known for its coastal location and beaches in the Cyclades.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509d39348190aa83304661230cba completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c746c9108190a1a81e94b4768f3c completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c929aec48190bb9a00b7086afe01 completed March 14, 2026, 8:46 p.m.
NED2 Entity disambiguation (via description) batch_69b5c993a9388190a52e573b013dbe29 completed March 14, 2026, 8:48 p.m.
Created at: March 12, 2026, 11:08 p.m.