Triple

T4821336
Position Surface form Disambiguated ID Type / Status
Subject Västergötland E107715 entity
Predicate containsCity P294 FINISHED
Object Borås E352932 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: Borås | Statement: [Västergötland, containsCity, Borås]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borås
Context triple: [Västergötland, containsCity, Borås]
  • A. Borås chosen
    Borås is a Swedish city known for its textile industry heritage, design and fashion focus, and location in western Sweden.
  • B. Västerås
    Västerås is a historic city in central Sweden known for its medieval cathedral, lakeside location on Lake Mälaren, and role as an important industrial and commercial center.
  • C. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • D. Skövde
    Skövde is a town in south-central Sweden that serves as a major military hub and training center for the Swedish Army.
  • E. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c99b46c8190b6fbcf9f98b9e993 completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfbd5d67c881909b57ead8968a840b completed March 22, 2026, 9:58 a.m.
Created at: March 20, 2026, 1:24 p.m.