Triple

T15427331
Position Surface form Disambiguated ID Type / Status
Subject Horsens E369544 entity
Predicate hasTwinTown P919 FINISHED
Object Sandefjord E113699 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: Sandefjord | Statement: [Horsens, hasTwinTown, Sandefjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandefjord
Context triple: [Horsens, hasTwinTown, Sandefjord]
  • A. Sandefjord chosen
    Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
  • B. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • C. Egersund
    Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
  • D. 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.
  • E. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec31f4881908b26ff7c381d7bc9 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a012ec19c508190912c3fe186f8a992 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 3:20 a.m.