Triple

T12749260
Position Surface form Disambiguated ID Type / Status
Subject Tai Yai E304686 entity
Predicate populationCenter P2106 FINISHED
Object Lashio E97789 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: Lashio | Statement: [Tai Yai, populationCenter, Lashio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lashio
Context triple: [Tai Yai, populationCenter, Lashio]
  • A. Lashio chosen
    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. Mawlamyine
    Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
  • C. Myingyan
    Myingyan is a town in central Myanmar known as a commercial and transport hub along the Irrawaddy River in the Mandalay Region.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd75f508190aaae0969f33d1523 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8e89cc8190ac97b13d9d409179 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:27 p.m.