Triple

T11806492
Position Surface form Disambiguated ID Type / Status
Subject University of Medicine, Mandalay E280758 entity
Predicate locatedIn 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: [University of Medicine, Mandalay, locatedIn, Mandalay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandalay
Context triple: [University of Medicine, Mandalay, locatedIn, 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. Pathein
    Pathein is a major city in Myanmar’s Ayeyarwady Region, known as a regional commercial hub and for its traditional handcrafted umbrellas.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5c8324481909a54852a9bb714e0 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f655515be48190a0793eef7b016852 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:42 p.m.