Triple

T721659
Position Surface form Disambiguated ID Type / Status
Subject Ledo Road E14629 entity
Predicate locatedIn P40 FINISHED
Object Myanmar 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: Myanmar | Statement: [Ledo Road, locatedIn, Myanmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myanmar
Context triple: [Ledo Road, locatedIn, Myanmar]
  • 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. Thailand
    Thailand is a Southeast Asian nation known for its rich Buddhist culture, constitutional monarchy, and role as a regional hub for tourism and trade.
  • 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. Laos
    Laos is a landlocked Southeast Asian country known for its mountainous terrain, Buddhist culture, and status as one of the region’s least developed but rapidly reforming economies.
  • 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_69a4934c753c81909b309027e48b9b3a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a591124c8190842e7ef18b064198 completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b83709248190bee17ec028b12bae completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:37 p.m.