Triple

T6414360
Position Surface form Disambiguated ID Type / Status
Subject CEVA line E127785 entity
Predicate locatedInCity P40 FINISHED
Object Annemasse E93133 NE FINISHED

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: Annemasse | Statement: [CEVA line, locatedInCity, Annemasse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annemasse
Context triple: [CEVA line, locatedInCity, Annemasse]
  • A. Annemasse chosen
    Annemasse is a French town in the Haute-Savoie department near the Swiss border, functioning as a key commuter suburb of Geneva and a regional transport hub.
  • B. Obernai
    Obernai is a historic Alsatian town in northeastern France known for its well-preserved medieval architecture, wine production, and picturesque setting along the Alsace Wine Route.
  • C. Sarreguemines
    Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
  • D. Armançon
    Armançon is a river in central-eastern France that flows through the Burgundy region before joining the Yonne River.
  • E. Mondorf-les-Bains
    Mondorf-les-Bains is a spa town in southeastern Luxembourg renowned for its thermal baths, wellness facilities, and casino.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068e6bd3881909b1979de5cdf17fb completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bb5196c8190ab970afbe4f2a672 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:42 p.m.