Triple

T7029610
Position Surface form Disambiguated ID Type / Status
Subject Cachar district E163236 entity
Predicate hasBorderWith P224 FINISHED
Object Manipur E40576 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: Manipur | Statement: [Cachar district, hasBorderWith, Manipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manipur
Context triple: [Cachar district, hasBorderWith, Manipur]
  • A. Manipur chosen
    Manipur is a northeastern Indian state known for its scenic hills and valleys, rich indigenous cultures, and capital city Imphal.
  • B. Nagaland
    Nagaland is a mountainous state in northeastern India known for its diverse indigenous Naga tribes, vibrant festivals, and rich cultural heritage.
  • C. Tripura
    Tripura is a small, hilly state in northeastern India known for its diverse tribal cultures, historical palaces, and dense forests.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e20dbc8c8190a7446290747d8078 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91b1532808190a0b85fa98ef24cfa completed March 29, 2026, 12:29 p.m.
Created at: March 27, 2026, 2:35 p.m.