Triple

T17726350
Position Surface form Disambiguated ID Type / Status
Subject Drammensregionen E442470 entity
Predicate containsMunicipality P852 FINISHED
Object Hurum 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: Hurum | Statement: [Drammensregionen, containsMunicipality, Hurum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurum
Context triple: [Drammensregionen, containsMunicipality, Hurum]
  • A. Hurum chosen
    Hurum is a former municipality in southeastern Norway, located on the Hurum Peninsula between the Oslofjord and Drammensfjord.
  • B. Orhaneli
    Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
  • C. Harur
    Harur is a town in the Indian state of Tamil Nadu known for its role as a local commercial and administrative center within the Dharmapuri region.
  • D. Ahlat
    Ahlat is a historic town in eastern Turkey renowned for its medieval Seljuk-era cemeteries and monuments on the northwestern shore of Lake Van.
  • E. Hansaray
    Hansaray is a historic Crimean Tatar palace complex in Bakhchisarai that served as the residence of the Crimean Khans and a major cultural and political center.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478e25a80819096289fba4ecb227f completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 10:07 a.m.