Triple

T10486436
Position Surface form Disambiguated ID Type / Status
Subject Garo people E247309 entity
Predicate recognizedInState P4733 FINISHED
Object Assam E4843 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: Assam | Statement: [Garo people, recognizedInState, Assam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Assam
Context triple: [Garo people, recognizedInState, Assam]
  • A. Assam chosen
    Assam is a northeastern region of the Indian subcontinent known for its tea plantations, rich biodiversity, and distinct cultural heritage.
  • B. Tripura
    Tripura is a small, hilly state in northeastern India known for its diverse tribal cultures, historical palaces, and dense forests.
  • C. 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.
  • D. West Bengal
    West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
  • E. Meghalaya
    Meghalaya is a hilly state in northeastern India known for its heavy rainfall, lush forests, and diverse indigenous cultures.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5190da7f081908c38b5964a567e37 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69de54d83e44819097abf6714bd48680 completed April 14, 2026, 2:53 p.m.
Created at: April 6, 2026, 12:23 p.m.