Triple

T20707814
Position Surface form Disambiguated ID Type / Status
Subject Jærbanen E508950 entity
Predicate connectsTo P845 FINISHED
Object Nærbø
Nærbø is a village in Hå municipality in Rogaland county, Norway, known as an agricultural center on the Jæren plain with rail connections to larger nearby cities.
E1497502 NE FINISHED

How this triple was built (4 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: Nærbø | Statement: [Jærbanen, connectsTo, Nærbø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nærbø
Context triple: [Jærbanen, connectsTo, Nærbø]
  • A. Austbø
    Austbø is a small settlement in the municipality of Alstahaug in Nordland county, Norway.
  • B. Sæbøvik
    Sæbøvik is a small village in western Norway located within the municipality of Kvinnherad in Vestland county.
  • C. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • D. Vedvik
    Vedvik is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
  • E. Bremanger
    Bremanger is a coastal municipality in Vestland county, Norway, known for its rugged fjord landscape, fishing communities, and scenic beaches like Grotlesanden.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nærbø
Triple: [Jærbanen, connectsTo, Nærbø]
Generated description
Nærbø is a village in Hå municipality in Rogaland county, Norway, known as an agricultural center on the Jæren plain with rail connections to larger nearby cities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nærbø
Target entity description: Nærbø is a village in Hå municipality in Rogaland county, Norway, known as an agricultural center on the Jæren plain with rail connections to larger nearby cities.
  • A. Austbø
    Austbø is a small settlement in the municipality of Alstahaug in Nordland county, Norway.
  • B. Sæbøvik
    Sæbøvik is a small village in western Norway located within the municipality of Kvinnherad in Vestland county.
  • C. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • D. Vedvik
    Vedvik is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
  • E. Bremanger
    Bremanger is a coastal municipality in Vestland county, Norway, known for its rugged fjord landscape, fishing communities, and scenic beaches like Grotlesanden.
  • F. None of above. chosen

Provenance (5 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_69e0b4c40ad88190b81f77695366d328 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1952e888190877b79933970f7b0 completed April 21, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a24970ea881908e0d585753357b24 completed May 17, 2026, 8:27 p.m.
NEDg Description generation batch_6a0a259145c0819082edd73cf9a8574b completed May 17, 2026, 8:31 p.m.
NED2 Entity disambiguation (via description) batch_6a0a25f766048190931de694fdc23931 completed May 17, 2026, 8:32 p.m.
Created at: April 16, 2026, 12:14 p.m.