Triple

T17659536
Position Surface form Disambiguated ID Type / Status
Subject Left Front (various states) E440212 entity
Predicate region P40 FINISHED
Object Tripura NE NERFINISHED

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: [Left Front (various states), region, Tripura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tripura
Context triple: [Left Front (various states), region, 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 (2 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46ea469448190b2753571f8493aef completed April 19, 2026, 5:56 a.m.
Created at: April 10, 2026, 9:40 a.m.