Triple

T1833872
Position Surface form Disambiguated ID Type / Status
Subject Kistna River E41019 entity
Predicate tributary 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: [Kistna River, tributary, Musi River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musi River
Context triple: [Kistna River, tributary, 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb02540dc819081b19a09562139cd completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1eec2a3f081909aa9f32ff5537a3c completed March 11, 2026, 10:37 p.m.
Created at: March 4, 2026, 7:33 p.m.