Triple

T4679719
Position Surface form Disambiguated ID Type / Status
Subject Eisenstadt E103768 entity
Predicate hasTwinTown P919 FINISHED
Object Colmar E44428 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: Colmar | Statement: [Eisenstadt, hasTwinTown, Colmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colmar
Context triple: [Eisenstadt, hasTwinTown, Colmar]
  • A. Colmar chosen
    Colmar is a picturesque historic town in northeastern France’s Alsace region, renowned for its well-preserved medieval and early Renaissance architecture and canals.
  • B. Colmar-Berg
    Colmar-Berg is a small town in central Luxembourg known for being the residence of the Grand Ducal family and the site of a major Goodyear tire factory.
  • C. Altkirch
    Altkirch is a small historic town in northeastern France that serves as an administrative and cultural center in the Alsace region.
  • D. Ribeauvillé
    Ribeauvillé is a historic wine-producing town in France’s Alsace region, known for its medieval architecture and location along the Alsace Wine Route.
  • E. Metz
    Metz is a historic city in northeastern France known for its Gothic Saint-Stephen Cathedral, Roman and medieval heritage, and role as the capital of the Moselle department in the Grand Est region.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd636c105081908655ab384f539f38 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf2196e8e88190b8da71ecfb07dfc8 completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:16 p.m.