Triple

T19739358
Position Surface form Disambiguated ID Type / Status
Subject Contrexéville E474071 entity
Predicate locatedNear P294 FINISHED
Object Vittel NE NERFINISHED

How this triple was built (2 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: Vittel | Statement: [Contrexéville, locatedNear, Vittel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vittel
Context triple: [Contrexéville, locatedNear, Vittel]
  • A. Vittel chosen
    Vittel is a French spa town renowned for its mineral water springs and bottled water brand, located in northeastern France.
  • B. Perrier
    Perrier is a French brand of naturally carbonated mineral water known for its distinctive green bottles and strong sparkling taste.
  • C. San Pellegrino
    San Pellegrino is an Italian brand best known for its naturally carbonated mineral water and flavored sparkling beverages.
  • D. Nestlé Waters
    Nestlé Waters is the bottled water division of Nestlé, responsible for producing and marketing a wide portfolio of still and sparkling water brands worldwide.
  • E. Schweppes
    Schweppes is a historic beverage brand best known for its carbonated soft drinks and tonic waters, now owned and marketed in many regions by The Coca-Cola Company.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e651607e388190bbb2aaed252820fe completed April 20, 2026, 4:16 p.m.
Created at: April 10, 2026, 1:47 p.m.