Triple

T13845534
Position Surface form Disambiguated ID Type / Status
Subject Votka River E332793 entity
Predicate mouth P407 FINISHED
Object Kama River E53216 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: Kama River | Statement: [Votka River, mouth, Kama River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kama River
Context triple: [Votka River, mouth, Kama River]
  • A. Kama River chosen
    The Kama River is a major waterway in western Russia that serves as one of the largest and most significant tributaries of the Volga River.
  • B. Kunene River
    The Kunene River is a major river in southwestern Africa that forms part of the border between Angola and Namibia and is known for features like the Epupa Falls.
  • C. Lek River
    The Lek River is a major distributary branch of the Rhine in the Netherlands, playing an important role in the country’s inland waterway network and flood management system.
  • D. Great Kwa River
    The Great Kwa River is a significant waterway in southeastern Nigeria known for its rich biodiversity and role in supporting local communities and ecosystems.
  • E. Sun Kosi River
    The Sun Kosi River is a major Himalayan river in eastern Nepal, renowned for its long white-water rafting expeditions and as a key tributary of the Koshi River 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b1a25c8190a9f85ba43c421188 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e72b9f08190a33e8e20541edd21 completed May 9, 2026, 12:23 a.m.
Created at: April 9, 2026, 10:13 p.m.