Triple

T14883048
Position Surface form Disambiguated ID Type / Status
Subject King Bagyidaw E350047 entity
Predicate territoryCeded P76587 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: [King Bagyidaw, territoryCeded, Manipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manipur
Context triple: [King Bagyidaw, territoryCeded, 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e7c0e48190af2d68a71130585c completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5af8208190a35451477ea20b03 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:56 a.m.