Triple

T15332045
Position Surface form Disambiguated ID Type / Status
Subject Stad E366558 entity
Predicate administrativeCentre P1474 FINISHED
Object Selje E1177343 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: Selje | Statement: [Stad, administrativeCentre, Selje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Selje
Context triple: [Stad, administrativeCentre, Selje]
  • A. Selje chosen
    Selje is a small coastal village and former municipality in western Norway, known for its scenic fjord landscape and the historic Selja Monastery ruins.
  • B. Seljord
    Seljord is a small Norwegian town known for its scenic lake, traditional cultural events, and the local legend of the Seljord Lake serpent.
  • C. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • D. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • E. Ullensvang
    Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001f7d79348190aba1889a7eb3d7c8 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 3:17 a.m.