Triple

T18060347
Position Surface form Disambiguated ID Type / Status
Subject Toungoo E432154 entity
Predicate romanization P2508 FINISHED
Object Taungoo NE NERFINISHED

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: [Toungoo, romanization, Taungoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taungoo
Context triple: [Toungoo, romanization, 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. Kengtung
    Kengtung is a historic town in eastern Myanmar’s Shan State, known as a cultural center of the Tai ethnic groups and a gateway to the Golden Triangle region.
  • D. 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.
  • E. Moulamein
    Moulamein is a small rural town in the Riverina region of New South Wales, Australia, known for its historic buildings and riverside setting.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c1066f508190bacf1122e366f87b completed April 19, 2026, 11:48 a.m.
Created at: April 10, 2026, 10:26 a.m.