Triple

T4219182
Position Surface form Disambiguated ID Type / Status
Subject Vestfold og Telemark E94296 entity
Predicate containsTown P847 FINISHED
Object Tønsberg E112118 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: Tønsberg | Statement: [Vestfold og Telemark, containsTown, Tønsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tønsberg
Context triple: [Vestfold og Telemark, containsTown, Tønsberg]
  • A. Tønsberg chosen
    Tønsberg is a historic coastal town in southeastern Norway, often regarded as one of the country’s oldest cities and known for its Viking heritage and maritime culture.
  • B. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • C. Nyborg
    Nyborg is a historic coastal town and former royal seat in central Denmark, located on the island of Funen.
  • D. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • E. Sandefjord
    Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34e0b2ee08190930600e1e802b325 completed March 12, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4df07a08190be5d2a516910c491 completed March 14, 2026, 10:44 p.m.
Created at: March 12, 2026, 11:04 p.m.