Triple

T23030048
Position Surface form Disambiguated ID Type / Status
Subject Homansbyen E573431 entity
Predicate hasNearbyArea P4647 FINISHED
Object Sentrum 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: Sentrum | Statement: [Homansbyen, hasNearbyArea, Sentrum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sentrum
Context triple: [Homansbyen, hasNearbyArea, 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. Centrum
    Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
  • C. Centrum
    Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
  • D. Centrum
    Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
  • E. Aure sentrum
    Aure sentrum is the main village and commercial hub of the Sykkylven municipality in Møre og Romsdal county, Norway.
  • 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f184803e908190b1e58545b9c3d587 completed April 29, 2026, 4:09 a.m.
Created at: April 17, 2026, 3:53 p.m.