Triple

T3910177
Position Surface form Disambiguated ID Type / Status
Subject Johann Olav Koss E87301 entity
Predicate placeOfBirth P1 FINISHED
Object Drammen E105261 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: Drammen | Statement: [Johann Olav Koss, placeOfBirth, Drammen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drammen
Context triple: [Johann Olav Koss, placeOfBirth, Drammen]
  • A. Drammen chosen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • B. Bærum
    Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
  • C. Gjøvik
    Gjøvik is a town and municipality in Innlandet county, Norway, known for its location along Lake Mjøsa and its mix of industrial heritage and modern sports and cultural facilities.
  • D. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • E. Sinsen
    Sinsen is a neighborhood and major transport hub in Oslo, Norway, known for its busy traffic interchange and public transit connections.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed3408f881908c3cffc5dbfe3950 completed March 9, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627a72da881908e1a4965177727eb completed March 15, 2026, 3:29 a.m.
Created at: March 9, 2026, 3:22 p.m.