Triple

T12348451
Position Surface form Disambiguated ID Type / Status
Subject Lost River E294418 entity
Predicate hasName P744 FINISHED
Object Lost River unclear NED1 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: Lost River | Statement: [Lost River, hasName, Lost River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lost River
Context triple: [Lost River, hasName, Lost River]
  • A. Lost River
    Lost River is a largely subterranean river in West Virginia known for disappearing underground and reemerging as the Cacapon River.
  • B. Lost River
    Lost River is a minor watercourse in New South Wales, Australia, that serves as a tributary of the Goodradigbee River within the Murray–Darling Basin.
  • C. Lost River
    Lost River is a 2014 fantasy-neo-noir film written and directed by Ryan Gosling, known for its surreal, dreamlike atmosphere and ensemble cast including Christina Hendricks.
  • D. Lost River
    Lost River is an intermittent river in southern Oregon and northern California known for its unusual looping course and role in regional irrigation and wildlife refuges.
  • E. Lost River
    Lost River is an underground river in Bowling Green, Kentucky, known for flowing through the Lost River Cave system and offering boat tours and geological attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f7ba17481908b03af7316b28d9b completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62aae8d7c8190a722c28a5a153d1d completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.