Triple

T20620615
Position Surface form Disambiguated ID Type / Status
Subject Flicka E506687 entity
Predicate setting P1957 FINISHED
Object Wyoming 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: Wyoming | Statement: [Flicka, setting, Wyoming]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wyoming
Context triple: [Flicka, setting, Wyoming]
  • A. Wyoming chosen
    Wyoming is a sparsely populated U.S. state known for its vast plains, the Rocky Mountains, and iconic national parks like Yellowstone and Grand Teton.
  • B. Wyoming
    Wyoming is a small borough in Luzerne County, Pennsylvania, situated in the historic Wyoming Valley along the Susquehanna River.
  • C. Wyoming
    Wyoming is a residential suburb on the Central Coast of New South Wales, Australia, known for its leafy streets, local shopping facilities, and proximity to Gosford.
  • D. Montana
    Montana was a former Swiss alpine resort municipality that later became part of the larger resort area of Crans-Montana in the canton of Valais.
  • E. Montana
    Montana is a small city in northwestern Bulgaria known as a regional administrative and economic center near the foothills of the Balkan Mountains.
  • 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe19ca481908c896bec49a025cd completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:42 a.m.