Triple

T7911282
Position Surface form Disambiguated ID Type / Status
Subject Zanskar Range E183703 entity
Predicate extendsInto P1673 FINISHED
Object Himachal Pradesh E15088 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: Himachal Pradesh | Statement: [Zanskar Range, extendsInto, Himachal Pradesh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Himachal Pradesh
Context triple: [Zanskar Range, extendsInto, Himachal Pradesh]
  • A. Himachal Pradesh chosen
    Himachal Pradesh is a mountainous state in northern India known for its Himalayan landscapes, hill stations, and tourism.
  • B. Uttarakhand
    Uttarakhand is a northern Indian state in the Himalayas known for its sacred rivers, pilgrimage sites, and mountainous landscapes.
  • C. Sikkim
    Sikkim is a small, mountainous Indian state in the eastern Himalayas known for its dramatic landscapes, Buddhist monasteries, and proximity to Mount Kanchenjunga.
  • D. Jammu and Kashmir
    Jammu and Kashmir is a northern region of the Indian subcontinent known for its mountainous terrain, strategic location, and long-standing political and territorial disputes.
  • E. Haryana
    Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
  • 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a725b8c8190a530adb3107a95dd completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc639b68a4819080acfca35e498cfa completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 5:04 p.m.