Triple

T1322749
Position Surface form Disambiguated ID Type / Status
Subject Reykjavík E28255 entity
Predicate hasDistrict P459 FINISHED
Object Grafarvogur E152159 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: Grafarvogur | Statement: [Reykjavík, hasDistrict, Grafarvogur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grafarvogur
Context triple: [Reykjavík, hasDistrict, Grafarvogur]
  • A. Reykvíkingur
    Reykvíkingur is the Icelandic term for a resident or native of Reykjavík, the capital city of Iceland.
  • B. Vágar
    Vágar is one of the main islands of the Faroe Islands, known for hosting the archipelago’s only airport and serving as a key transport hub.
  • C. Gardar
    Gardar was the principal ecclesiastical and administrative center of the Norse settlements in medieval Greenland, serving as the seat of the bishopric.
  • D. Laugardalur chosen
    Laugardalur is a district in Reykjavík, Iceland, known for its large recreational area featuring parks, sports facilities, and the city’s main geothermal swimming pool.
  • E. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19b76b48190aa8857b80971a842 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62764d88190b7d1fca10835f560 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.