Triple

T1381579
Position Surface form Disambiguated ID Type / Status
Subject Emden E29348 entity
Predicate hasTwinTown P919 FINISHED
Object Haugesund E75231 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: Haugesund | Statement: [Emden, hasTwinTown, Haugesund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haugesund
Context triple: [Emden, hasTwinTown, Haugesund]
  • A. Haugesund chosen
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • B. Nordfjordeid
    Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
  • C. Sandefjord
    Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
  • D. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • E. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c31b176c8190a896183140c5c8be completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69addf2374ac8190ac2a2a753c056a3d completed March 8, 2026, 8:42 p.m.
Created at: March 1, 2026, 7:59 p.m.