Triple

T9961086
Position Surface form Disambiguated ID Type / Status
Subject Aasmund Olavsson Vinje E195568 entity
Predicate notableWork P4 FINISHED
Object Storegut E831924 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: Storegut | Statement: [Aasmund Olavsson Vinje, notableWork, Storegut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Storegut
Context triple: [Aasmund Olavsson Vinje, notableWork, Storegut]
  • A. Storegut chosen
    Storegut is a narrative poem by Norwegian writer Aasmund Olavsson Vinje that portrays rural life and folk culture in 19th-century Norway.
  • B. Stash
    Stash is a U.S.-based fintech company that offers an app for simplified investing, banking, and financial education for everyday consumers.
  • C. Storelva
    Storelva is a river in Ringerike, Norway, known locally as a small watercourse within the region’s inland river system.
  • D. Stod
    Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • E. Steng
    Steng is the family name of Austrian actor and director Klaus Maria Brandauer, known for his acclaimed performances in European cinema and Hollywood films.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d219c48190b2084b0eb07ae125 completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257aa73d4819081f77f8386449905 completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:47 p.m.