Triple

T4071684
Position Surface form Disambiguated ID Type / Status
Subject All India Forward Bloc E86661 entity
Predicate activeIn P1560 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: [All India Forward Bloc, activeIn, Tripura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tripura
Context triple: [All India Forward Bloc, activeIn, 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc20ed788190bd935082a348a05d completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b66b25d00481909eaf22c7c797c3f1 completed March 15, 2026, 8:17 a.m.
Created at: March 9, 2026, 3:38 p.m.