Triple

T15903025
Position Surface form Disambiguated ID Type / Status
Subject Wagaung E385635 entity
Predicate hasScriptName P60557 FINISHED
Object ဝါခေါင်
ဝါခေါင် သည် မြန်မာလူမျိုးတို့၏ ပဉ္စမ လဆန်းလအဖြစ် သုံးစွဲသည့် ရာသီဥတုနှင့် ဘာသာရေးအရေးပါမှုများ ပါဝင်သည့် မြန်မာလကန်ရဲ့ တစ်လဖြစ်သည်။
 E1183428 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: ဝါခေါင် | Statement: [Wagaung, hasScriptName, ဝါခေါင်]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ဝါခေါင်
Context triple: [Wagaung, hasScriptName, ဝါခေါင်]
  • A. Wun Wun
    Wun Wun is a giant allied with Jon Snow in Game of Thrones, known for his immense strength and pivotal role in key battles.
  • B. Wazhazhe
    Wazhazhe is the self-designation of the Osage people, a Native American nation originally from the central United States.
  • C. Wunna
    Wunna is a studio album by American rapper Gunna that helped solidify his mainstream success with its melodic trap sound and chart-topping performance.
  • D. Na Wa Ta
    Na Wa Ta is the Burmese-language acronym for Myanmar’s former military junta, the State Law and Order Restoration Council, which ruled the country after the 1988 coup.
  • E. Wapengo
    Wapengo is a small coastal locality in New South Wales, Australia, known for its proximity to Wapengo Lake and its oyster farming industry.
  • 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: ဝါခေါင်
Triple: [Wagaung, hasScriptName, ဝါခေါင်]
Generated description
ဝါခေါင် သည် မြန်မာလူမျိုးတို့၏ ပဉ္စမ လဆန်းလအဖြစ် သုံးစွဲသည့် ရာသီဥတုနှင့် ဘာသာရေးအရေးပါမှုများ ပါဝင်သည့် မြန်မာလကန်ရဲ့ တစ်လဖြစ်သည်။
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ဝါခေါင်
Target entity description: ဝါခေါင် သည် မြန်မာလူမျိုးတို့၏ ပဉ္စမ လဆန်းလအဖြစ် သုံးစွဲသည့် ရာသီဥတုနှင့် ဘာသာရေးအရေးပါမှုများ ပါဝင်သည့် မြန်မာလကန်ရဲ့ တစ်လဖြစ်သည်။
  • A. Wun Wun
    Wun Wun is a giant allied with Jon Snow in Game of Thrones, known for his immense strength and pivotal role in key battles.
  • B. Wazhazhe
    Wazhazhe is the self-designation of the Osage people, a Native American nation originally from the central United States.
  • C. Wunna
    Wunna is a studio album by American rapper Gunna that helped solidify his mainstream success with its melodic trap sound and chart-topping performance.
  • D. Na Wa Ta
    Na Wa Ta is the Burmese-language acronym for Myanmar’s former military junta, the State Law and Order Restoration Council, which ruled the country after the 1988 coup.
  • E. Wapengo
    Wapengo is a small coastal locality in New South Wales, Australia, known for its proximity to Wapengo Lake and its oyster farming industry.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563e79608190a1fdfe6265817616 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb051a05081908c349cd9a1ff247a completed May 9, 2026, 10:08 p.m.
NEDg Description generation batch_69ffb1742e2c8190ab7fd714a8f38312 completed May 9, 2026, 10:13 p.m.
NED2 Entity disambiguation (via description) batch_69ffb1eedaf481908d70e3517fbd5492 completed May 9, 2026, 10:15 p.m.
Created at: April 10, 2026, 4:52 a.m.