Triple

T20980721
Position Surface form Disambiguated ID Type / Status
Subject XGD E516752 entity
Predicate locatedInCity P40 FINISHED
Object Arendal 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: Arendal | Statement: [XGD, locatedInCity, Arendal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arendal
Context triple: [XGD, locatedInCity, Arendal]
  • A. Arendal chosen
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • B. Nysted
    Nysted is a small coastal town in southeastern Denmark known for its historic harbor, medieval church, and proximity to the Baltic Sea.
  • C. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • D. Henningsvær
    Henningsvær is a picturesque fishing village in northern Norway, known for its traditional architecture, dramatic coastal scenery, and vibrant arts and tourism scene.
  • E. Tønsberg
    Tønsberg is a historic coastal town in southeastern Norway, often regarded as one of the country’s oldest cities and known for its Viking heritage and maritime culture.
  • 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_69e0b4ffac148190bbade9f0eceb660b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fbdd89f48190b58c67cc1f7968c0 completed April 21, 2026, 4:23 a.m.
Created at: April 16, 2026, 1:47 p.m.