Triple

T367114
Position Surface form Disambiguated ID Type / Status
Subject A35 motorway (France) E7984 entity
Predicate servesCity P82 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: [A35 motorway (France), servesCity, Colmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colmar
Context triple: [A35 motorway (France), servesCity, 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. Mulhouse
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • C. Thionville
    Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
  • D. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • E. Haguenau
    Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebe92c7c8190b49af2b2b461eacc completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5692e9f248190945be16aac260038 completed March 2, 2026, 10:40 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.