Triple

T5840421
Position Surface form Disambiguated ID Type / Status
Subject Tune ship E129578 entity
Predicate discoveredNear P8203 FINISHED
Object Sarpsborg E50822 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: Sarpsborg | Statement: [Tune ship, discoveredNear, Sarpsborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarpsborg
Context triple: [Tune ship, discoveredNear, Sarpsborg]
  • A. Sarpsborg chosen
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
  • B. Porsgrunn
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • C. 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.
  • D. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • E. Hønefoss
    Hønefoss is a Norwegian town known as a regional commercial and transport hub, situated along the Begna River northwest of Oslo.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d6f09c81908dfb3c2c51a2f5a9 completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6636b8a388190879829af44325e0e completed March 27, 2026, 11 a.m.
Created at: March 22, 2026, 3:54 p.m.