Triple

T4985012
Position Surface form Disambiguated ID Type / Status
Subject Trinamool Congress E111978 entity
Predicate regionOfActivity P82 FINISHED
Object Tripura E41565 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: Tripura | Statement: [Trinamool Congress, regionOfActivity, Tripura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tripura
Context triple: [Trinamool Congress, regionOfActivity, Tripura]
  • A. Tripura chosen
    Tripura is a small, hilly state in northeastern India known for its diverse tribal cultures, historical palaces, and dense forests.
  • B. Assam
    Assam is a northeastern region of the Indian subcontinent known for its tea plantations, rich biodiversity, and distinct cultural heritage.
  • C. Manipur
    Manipur is a northeastern Indian state known for its scenic hills and valleys, rich indigenous cultures, and capital city Imphal.
  • D. Meghalaya
    Meghalaya is a hilly state in northeastern India known for its heavy rainfall, lush forests, and diverse indigenous cultures.
  • E. Mizoram
    Mizoram is a hilly, forested state in northeastern India known for its Mizo culture, high literacy rate, and scenic landscapes along the border with Myanmar and Bangladesh.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd725766d88190b6fda860a005ce4e completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea46e3ad88190a61d50fc430e3131 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:33 p.m.