Triple

T5290658
Position Surface form Disambiguated ID Type / Status
Subject Vy regional trains E119732 entity
Predicate serves P98 FINISHED
Object Stavanger E74350 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: Stavanger | Statement: [Vy regional trains, serves, Stavanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stavanger
Context triple: [Vy regional trains, serves, Stavanger]
  • A. Stavanger chosen
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • B. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • C. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • D. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • E. Bergen
    Bergen is a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfc834be9081909cd2a11e76ebd3c8 completed March 22, 2026, 10:45 a.m.
Created at: March 20, 2026, 1:52 p.m.