Triple

T20250138
Position Surface form Disambiguated ID Type / Status
Subject Porsgrunn municipality E498529 entity
Predicate administrativeCentre P1474 FINISHED
Object Porsgrunn town NE NERFINISHED

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: Porsgrunn town | Statement: [Porsgrunn municipality, administrativeCentre, Porsgrunn town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porsgrunn town
Context triple: [Porsgrunn municipality, administrativeCentre, Porsgrunn town]
  • A. Porsgrunn chosen
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • B. Melbu
    Melbu is a small coastal village and fishing community in Hadsel Municipality in Nordland county, Norway.
  • C. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • D. Lyngdal
    Lyngdal is a coastal town and municipality in southern Norway known for its beaches, fjords, and tourism.
  • E. Nittedal
    Nittedal is a municipality in Viken county, Norway, known for its forested landscapes and role as a commuter area north of Oslo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a79a208190a5a7c0f6515bc393 completed April 20, 2026, 6:42 p.m.
Created at: April 11, 2026, 11:41 p.m.