Triple

T4657809
Position Surface form Disambiguated ID Type / Status
Subject Hedmark E102451 entity
Predicate hasMunicipality P847 FINISHED
Object Hamar E68670 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: Hamar | Statement: [Hedmark, hasMunicipality, Hamar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamar
Context triple: [Hedmark, hasMunicipality, Hamar]
  • A. Hamar chosen
    Hamar is a town and municipality in Innlandet county, Norway, known for its rich Viking history and as a regional cultural and administrative center.
  • B. Sassoun
    Sassoun is a mountainous region in historic Western Armenia, famed in Armenian folklore as the homeland of the legendary heroes of the national epic.
  • C. Hadrut
    Hadrut is a town in the Nagorno-Karabakh region, historically part of the Shusha uezd, known for its strategic location and role in regional conflicts between Armenia and Azerbaijan.
  • D. Hatti
    Hatti was an ancient Anatolian kingdom and cultural region centered in central Turkey, later absorbed into the Hittite Empire.
  • E. Kamorta
    Kamorta is a significant inhabited island and settlement in India’s Nicobar archipelago, known for its strategic location and indigenous Nicobarese communities.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd631a855c81909773737fd238a14d completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0378825881908fe3214f60be579e completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:15 p.m.