Triple

T4172633
Position Surface form Disambiguated ID Type / Status
Subject Mandalay Prison E86398 entity
Predicate city P40 FINISHED
Object Mandalay E57185 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: Mandalay | Statement: [Mandalay Prison, city, Mandalay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandalay
Context triple: [Mandalay Prison, city, Mandalay]
  • A. Mandalay chosen
    Mandalay is a major cultural and economic center in central Myanmar, historically known as the last royal capital of the Burmese kingdom.
  • B. Yangon
    Yangon is Myanmar’s largest city and former capital, known as a major commercial hub featuring a mix of colonial architecture and prominent Buddhist landmarks like the Shwedagon Pagoda.
  • C. 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.
  • D. 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.
  • E. Taunggyi
    Taunggyi is a major city in eastern Myanmar known as an administrative, cultural, and commercial center in the Shan region.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e65b548190be095df62091b960 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589f001e48190a4c5aab6cfd29ffb completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:45 p.m.