Triple

T560556
Position Surface form Disambiguated ID Type / Status
Subject Hyderabad E13440 entity
Predicate locatedOnRiver P165 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: [Hyderabad, locatedOnRiver, Musi River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musi River
Context triple: [Hyderabad, locatedOnRiver, 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. 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.
  • C. Adhaim River
    The Adhaim River is a significant river in Iraq that flows through the northeastern part of the country before joining the Tigris.
  • D. Shashe River
    The Shashe River is a significant watercourse in southern Africa that flows through Botswana and Zimbabwe before joining the Limpopo River.
  • E. Limmat River
    The Limmat River is a major Swiss waterway that flows out of Lake Zurich and runs through the city of Zurich before joining the Aare River.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499e2795c8190903240e79964156d completed March 1, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3b93323c8190948dd9993a468a78 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:32 p.m.