Triple

T5406174
Position Surface form Disambiguated ID Type / Status
Subject Agder E120897 entity
Predicate containsTown P847 FINISHED
Object Tvedestrand E346169 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: Tvedestrand | Statement: [Agder, containsTown, Tvedestrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tvedestrand
Context triple: [Agder, containsTown, Tvedestrand]
  • A. Tvedestrand chosen
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • B. Steinkjer
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • C. Skien
    Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
  • D. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
  • E. Balestrand
    Balestrand is a picturesque village in western Norway known for its fjordside scenery, historic wooden hotels, and role as a gateway to exploring the Sognefjord region.
  • 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_69bd46391c0c81909fa484446732b6a3 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87924c588190beb4a1be27f8d11b completed March 20, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107a4786881908a5fdd26e65e949b completed March 23, 2026, 9:28 a.m.
Created at: March 20, 2026, 2:05 p.m.