Triple

T21334009
Position Surface form Disambiguated ID Type / Status
Subject Rough River E525988 entity
Predicate hasMouthIn P1008 FINISHED
Object Green River 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: Green River | Statement: [Rough River, hasMouthIn, Green River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green River
Context triple: [Rough River, hasMouthIn, Green River]
  • A. Green River
    The Green River is a major tributary of the Colorado River that flows through Wyoming, Utah, and Colorado, carving deep canyons and shaping much of the Colorado Plateau’s dramatic landscape.
  • B. Green River
    The Green River is a mountain river in British Columbia, Canada, known for flowing near the Fitzsimmons Range and through the Whistler area.
  • C. Green River
    Green River is a small city in southwestern Wyoming that serves as the county seat of Sweetwater County and is known for its location along the Green River and nearby rock formations.
  • D. Green River chosen
    Green River is a significant waterway in Kentucky known for its ecological diversity, recreational opportunities, and historical importance in the region’s river transport and settlement.
  • E. Green River
    Green River is a series of site-specific environmental art interventions by Olafur Eliasson in which he temporarily dyed urban rivers bright green to provoke reflection on perception, nature, and public space.
  • 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_69e0b51b90788190a4dd823d962626da completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5ba65c4081908b93d5dc6a937cb6 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 4:43 p.m.