Triple

T1231468
Position Surface form Disambiguated ID Type / Status
Subject Grozny E26451 entity
Predicate locatedOnRiver P165 FINISHED
Object Sunzha River E146725 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: Sunzha River | Statement: [Grozny, locatedOnRiver, Sunzha River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sunzha River
Context triple: [Grozny, locatedOnRiver, Sunzha River]
  • A. Sunzha River chosen
    The Sunzha River is a significant waterway in the North Caucasus that flows through Chechnya and neighboring regions, serving as an important tributary of the Terek River.
  • B. Xin’an River
    The Xin’an River is a major river in eastern China known for its scenic landscapes and as an important tributary contributing to the Qiantang River system.
  • C. Jialing River
    The Jialing River is a significant river in southwestern China that flows through Sichuan and Chongqing, contributing heavily to the region’s water resources, transportation, and ecology.
  • D. Luoqing River
    The Luoqing River is a regional river in Guangxi, China, that flows through and helps shape the city of Liuzhou.
  • E. Nanfei River
    The Nanfei River is a key waterway flowing through the city of Hefei in Anhui Province, China, playing an important role in its 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be5a25348190a0665b6324c4d8f5 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad7967a0fc8190822b70438f0b2c35 completed March 8, 2026, 1:28 p.m.
Created at: March 1, 2026, 7:47 p.m.