Triple

T9406427
Position Surface form Disambiguated ID Type / Status
Subject Bago Region E226598 entity
Predicate contains P35 FINISHED
Object Taungoo E432154 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: Taungoo | Statement: [Bago Region, contains, Taungoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taungoo
Context triple: [Bago Region, contains, Taungoo]
  • A. Lashio
    Lashio is a key town in northern Myanmar that historically served as an important transport and trade hub, particularly during World War II as the inland gateway to the Burma Road.
  • B. Taunggyi
    Taunggyi is a major city in eastern Myanmar known as an administrative, cultural, and commercial center in the Shan region.
  • C. Toungoo chosen
    Toungoo is a historic city in Myanmar that served as the capital of a powerful Burmese dynasty and a key military and trading center in the region.
  • D. Moulamein
    Moulamein is a small rural town in the Riverina region of New South Wales, Australia, known for its historic buildings and riverside setting.
  • E. Amarapura
    Amarapura is a former royal city in Myanmar renowned for its role as an early Burmese capital and for landmarks such as the U Bein Bridge.
  • 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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51c3fc988190ac34cc9e09f8ebfc completed April 1, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1102414e8819097a1bb58a3ded630 completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:47 p.m.