Triple

T2744369
Position Surface form Disambiguated ID Type / Status
Subject Operation Dracula E60830 entity
Predicate location P40 FINISHED
Object Rangoon E42684 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: Rangoon | Statement: [Operation Dracula, location, Rangoon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rangoon
Context triple: [Operation Dracula, location, Rangoon]
  • A. Yangon chosen
    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.
  • B. Mandalay
    Mandalay is a major cultural and economic center in central Myanmar, historically known as the last royal capital of the Burmese kingdom.
  • 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. Sittwe
    Sittwe is a coastal city in western Myanmar that has been a focal point of political unrest and ethnic tensions, including major protests during the Saffron Revolution.
  • 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_69ab4b79846081909096725374d65ce9 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb32ef74819096ae399d16d4f31d completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbcebe788190aa2b40158b64b7b2 completed March 10, 2026, 6:35 a.m.
Created at: March 6, 2026, 9:56 p.m.