Triple

T12354836
Position Surface form Disambiguated ID Type / Status
Subject Philip Christison E294583 entity
Predicate theatreOfOperations P710 FINISHED
Object Burma E11632 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: Burma | Statement: [Philip Christison, theatreOfOperations, Burma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burma
Context triple: [Philip Christison, theatreOfOperations, Burma]
  • A. Myanmar chosen
    Myanmar is a Southeast Asian nation bordered by India, China, and Thailand, known for its diverse ethnic groups, Buddhist heritage, and long history of military rule and political turmoil.
  • B. Burma (until 1937)
    Burma (until 1937) was a province administered as part of British India under British colonial rule before becoming a separately governed colony.
  • C. Thayarwady
    Thayarwady is a town in central Myanmar known as an administrative and commercial center within the Bago Region.
  • D. Arakan
    Arakan is a historical coastal region in western Myanmar, now largely corresponding to Rakhine State and known for its distinct ethnic and cultural identity.
  • E. India and Myanmar
    India and Myanmar are neighboring South and Southeast Asian countries that share a long, culturally diverse land border shaped by mountainous terrain and historical trade routes.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8bc60c8190b0ceb84093e70db4 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ab2dc30819082b12fa35f585762 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:54 p.m.