Triple

T11123176
Position Surface form Disambiguated ID Type / Status
Subject Macas E263067 entity
Predicate nearRiver P350 FINISHED
Object Upano River E322467 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: Upano River | Statement: [Macas, nearRiver, Upano River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Upano River
Context triple: [Macas, nearRiver, Upano River]
  • A. Upano River chosen
    The Upano River is a major river in eastern Ecuador that flows through the Andean foothills and Amazonian lowlands, known for its scenic valleys and whitewater rafting.
  • B. Aruwimi River
    The Aruwimi River is a significant river in the Democratic Republic of the Congo, known for flowing through dense equatorial rainforest and contributing substantially to the Congo River basin.
  • C. Nippara River
    Nippara River is a scenic mountain river in the Okutama region of western Tokyo, known for its clear waters, deep valleys, and surrounding limestone caves.
  • D. Yuruari River
    The Yuruari River is a tributary waterway in southeastern Venezuela that feeds into the Caroní River within the Guiana Shield region.
  • E. Hassamu River
    Hassamu River is a waterway flowing through the Nishi ward of Sapporo in Hokkaido, Japan, contributing to the area's urban landscape and drainage system.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7e82e933481908550499cf9dd6531 completed April 9, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef311c4819094b6b08a62d3afb3 completed May 3, 2026, 7:53 a.m.
Created at: April 8, 2026, 9:28 p.m.