Triple

T9785568
Position Surface form Disambiguated ID Type / Status
Subject Limbu E237483 entity
Predicate ethnicGroupOf P1898 FINISHED
Object Sikkim E177807 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: Sikkim | Statement: [Limbu, ethnicGroupOf, Sikkim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sikkim
Context triple: [Limbu, ethnicGroupOf, Sikkim]
  • A. Sikkim chosen
    Sikkim is a small, mountainous Indian state in the eastern Himalayas known for its dramatic landscapes, Buddhist monasteries, and proximity to Mount Kanchenjunga.
  • B. Meghalaya
    Meghalaya is a hilly state in northeastern India known for its heavy rainfall, lush forests, and diverse indigenous cultures.
  • C. Himachal Pradesh
    Himachal Pradesh is a mountainous state in northern India known for its Himalayan landscapes, hill stations, and tourism.
  • D. Uttarakhand
    Uttarakhand is a northern Indian state in the Himalayas known for its sacred rivers, pilgrimage sites, and mountainous landscapes.
  • E. Arunachal Pradesh
    Arunachal Pradesh is a northeastern Indian state known for its mountainous terrain, diverse indigenous cultures, and strategic location along the borders with China, Bhutan, and Myanmar.
  • 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_69ca84da927881909bda80caecad6010 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda2107f688190b2cab1509c508319 completed April 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69d23ceca020819080f310f84669551a completed April 5, 2026, 10:43 a.m.
Created at: March 30, 2026, 8:27 p.m.