Triple

T6762292
Position Surface form Disambiguated ID Type / Status
Subject Vegårshei E154623 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Tvedestrand E346169 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: Tvedestrand | Statement: [Vegårshei, neighboringMunicipality, Tvedestrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tvedestrand
Context triple: [Vegårshei, neighboringMunicipality, Tvedestrand]
  • A. Tvedestrand chosen
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • B. Holmestrand
    Holmestrand is a coastal town and municipality in Vestfold, Norway, known for its harbor, steep hillsides, and role as a regional transport hub along the Oslofjord.
  • C. Steinkjer
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • D. Skien
    Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
  • E. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d21444dc8190a290af86c81e96a5 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9061709f48190a9e198dac225aed4 completed March 29, 2026, 10:59 a.m.
Created at: March 27, 2026, 2:12 p.m.