Triple

T1916415
Position Surface form Disambiguated ID Type / Status
Subject Krishna River basin E40027 entity
Predicate hasTributary P415 FINISHED
Object Musi River E79170 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: Musi River | Statement: [Krishna River basin, hasTributary, Musi River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musi River
Context triple: [Krishna River basin, hasTributary, Musi River]
  • A. Musi River chosen
    The Musi River is a significant river in the Deccan region of India that flows through the city of Hyderabad, historically shaping its development and water supply.
  • B. Musi River
    The Musi River is a major river in southern Sumatra, Indonesia, that flows through the city of Palembang and serves as an important transportation and economic lifeline for the region.
  • C. Sura River
    The Sura River is a significant river in western Russia that flows through the Volga Upland and several regions before joining the Volga River.
  • D. Siul River
    The Siul River is a lesser-known river in the northern Indian subcontinent that feeds into the Ravi River within the Indus River basin.
  • E. Olza River
    The Olza River is a Central European river that flows through the historical region of Cieszyn Silesia, forming part of the border between Poland and the Czech Republic.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb20f54848190b9457e1231aa49db completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4b980888190a7df10662789f61e completed March 14, 2026, 4:31 a.m.
Created at: March 4, 2026, 7:35 p.m.