Triple

T5790629
Position Surface form Disambiguated ID Type / Status
Subject Gamle Oslo E128382 entity
Predicate hasNeighbouringBorough P16160 FINISHED
Object Sentrum E26400 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: Sentrum | Statement: [Gamle Oslo, hasNeighbouringBorough, Sentrum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sentrum
Context triple: [Gamle Oslo, hasNeighbouringBorough, Sentrum]
  • A. Sentrum chosen
    Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
  • B. Centrale
    Centrale is a major shopping centre located in the London Borough of Croydon, featuring a wide range of retail stores and services.
  • C. Centrale
    Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
  • D. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • E. Sandvika
    Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5585788190821b8da40259e0e7 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09820f5c08190811e848eb44ce5b9 completed March 23, 2026, 1:32 a.m.
Created at: March 22, 2026, 3:51 p.m.