Triple

T16177858
Position Surface form Disambiguated ID Type / Status
Subject Bhamo E392610 entity
Predicate hasAlternativeName P39 FINISHED
Object Banmaw
Banmaw, also known as Bhamo, is a strategic river port city in northern Myanmar’s Kachin State near the border with China.
E1199850 NE FINISHED

How this triple was built (4 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: Banmaw | Statement: [Bhamo, hasAlternativeName, Banmaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banmaw
Context triple: [Bhamo, hasAlternativeName, Banmaw]
  • A. Mawlamyine
    Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
  • B. Maungdaw
    Maungdaw is a town in Myanmar’s Rakhine State near the border with Bangladesh, known for its ethnically diverse population and its role in regional trade and migration.
  • 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. Kawthaung
    Kawthaung is a coastal town in southern Myanmar that serves as a key gateway for cross-border trade and travel with Thailand.
  • E. Nyaungshwe
    Nyaungshwe is a popular lakeside town in Myanmar that serves as the main gateway and tourist hub for visiting Inle Lake in Shan State.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Banmaw
Triple: [Bhamo, hasAlternativeName, Banmaw]
Generated description
Banmaw, also known as Bhamo, is a strategic river port city in northern Myanmar’s Kachin State near the border with China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Banmaw
Target entity description: Banmaw, also known as Bhamo, is a strategic river port city in northern Myanmar’s Kachin State near the border with China.
  • A. Mawlamyine
    Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
  • B. Maungdaw
    Maungdaw is a town in Myanmar’s Rakhine State near the border with Bangladesh, known for its ethnically diverse population and its role in regional trade and migration.
  • 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. Kawthaung
    Kawthaung is a coastal town in southern Myanmar that serves as a key gateway for cross-border trade and travel with Thailand.
  • E. Nyaungshwe
    Nyaungshwe is a popular lakeside town in Myanmar that serves as the main gateway and tourist hub for visiting Inle Lake in Shan State.
  • F. None of above. chosen

Provenance (5 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22059e7048190b4592cb1516b5f8d completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffefe4dc08190a6cc43a448ae6554 completed May 10, 2026, 3:43 a.m.
NEDg Description generation batch_6a0000a8a74c8190925c4140cf4a8520 completed May 10, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_6a0004ceda8c8190a358f58f76116a7f completed May 10, 2026, 4:08 a.m.
Created at: April 10, 2026, 5:02 a.m.