Triple

T15212043
Position Surface form Disambiguated ID Type / Status
Subject Carl Anton Larsen E363538 entity
Predicate placeOfBirth P1 FINISHED
Object Larvik E149637 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: Larvik | Statement: [Carl Anton Larsen, placeOfBirth, Larvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larvik
Context triple: [Carl Anton Larsen, placeOfBirth, Larvik]
  • A. Larvik chosen
    Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
  • B. Lyngdal
    Lyngdal is a coastal town and municipality in southern Norway known for its beaches, fjords, and tourism.
  • C. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • D. Levanger
    Levanger is a historic town and municipality in Trøndelag county, Norway, known for its traditional wooden architecture and role as a regional commercial and educational center.
  • E. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076c9e2481909d7a464b2172f4bf completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01dc23d081908ad6985bae5741ce completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 3:11 a.m.