Triple

T3738781
Position Surface form Disambiguated ID Type / Status
Subject NEVS E79648 entity
Predicate basedIn P40 FINISHED
Object Trollhättan E18308 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: Trollhättan | Statement: [NEVS, basedIn, Trollhättan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trollhättan
Context triple: [NEVS, basedIn, Trollhättan]
  • A. Trollhättan chosen
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • B. Skellefteå
    Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • D. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • E. Hudiksvall
    Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
  • 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb404b908190b6b4ee583dee3cc9 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6786a558819098973b8f10b7e7cb completed March 20, 2026, 3:28 p.m.
Created at: March 8, 2026, 3:34 p.m.