Triple

T5587066
Position Surface form Disambiguated ID Type / Status
Subject Sukhna Lake E146781 entity
Predicate waterSource P4102 FINISHED
Object Sukhna Choe E528778 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: Sukhna Choe | Statement: [Sukhna Lake, waterSource, Sukhna Choe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sukhna Choe
Context triple: [Sukhna Lake, waterSource, Sukhna Choe]
  • A. Sukhna Choe chosen
    Sukhna Choe is a seasonal stream in Chandigarh, India, that feeds and helps sustain the man-made Sukhna Lake.
  • B. Wang Chhu
    Wang Chhu is a significant river in western Bhutan that flows south into India, supporting agriculture, hydropower, and settlements along its valley.
  • C. Mo Chhu
    Mo Chhu is a major river in western Bhutan that flows through the Punakha Valley and contributes significantly to the country’s river system and hydropower resources.
  • D. Kongde Ri
    Kongde Ri is a prominent Himalayan peak in Nepal known for its striking multi-summited massif overlooking the Everest region.
  • E. Pak Yong
    Pak Yong is a stock male character in the traditional Malay dance-drama Mak Yong, often portrayed as a comic or supporting figure.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0209d713081908b39ee8befb2faf7 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d2f8710819094f5d052b767b9a6 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:38 p.m.