Triple

T3145340
Position Surface form Disambiguated ID Type / Status
Subject Hamar municipality E65749 entity
Predicate contains P35 FINISHED
Object town of Hamar E68670 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: town of Hamar | Statement: [Hamar municipality, contains, town of Hamar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Hamar
Context triple: [Hamar municipality, contains, town of Hamar]
  • A. Hamar municipality
    Hamar municipality is a local government area in Innlandet county, Norway, centered on the town of Hamar by Lake Mjøsa and known for its cultural, administrative, and sporting facilities.
  • B. Hamar chosen
    Hamar is a town and municipality in Innlandet county, Norway, known for its rich Viking history and as a regional cultural and administrative center.
  • C. Evenes Municipality
    Evenes Municipality is a small coastal municipality in Nordland county, Norway, known for its scenic fjord landscapes and proximity to the Ofotfjord.
  • D. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • E. Östhammar
    Östhammar is a small coastal town and municipality in eastern Sweden known for its archipelago, historic wooden buildings, and proximity to the Forsmark nuclear power plant.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59797788190a8d71262888c5df0 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224f18e80819083be53c556d56947 completed March 12, 2026, 2:29 a.m.
Created at: March 8, 2026, 3:05 p.m.