Triple

T22237913
Position Surface form Disambiguated ID Type / Status
Subject Hasle harbor E549639 entity
Predicate locatedIn P40 FINISHED
Object Hasle NE NERFINISHED

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: Hasle | Statement: [Hasle harbor, locatedIn, Hasle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasle
Context triple: [Hasle harbor, locatedIn, Hasle]
  • A. Hasle chosen
    Hasle is a small coastal town on the Danish island of Bornholm, known for its historic harbor, smoked herring, and scenic Baltic Sea surroundings.
  • B. Haslum
    Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
  • C. Hassel
    Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
  • D. Hassela
    Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
  • E. Hasselager
    Hasselager is a residential neighborhood in the southern part of Aarhus, Denmark.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f13210eb9c8190bc40d06c393e0d9a completed April 28, 2026, 10:17 p.m.
Created at: April 16, 2026, 8:38 p.m.