Triple
T252247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynthia Maung |
E5174
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Maung
Maung is a Burmese surname commonly used in Myanmar and among the Burmese diaspora.
|
E32253
|
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: Maung | Statement: [Cynthia Maung, familyName, Maung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maung Context triple: [Cynthia Maung, familyName, Maung]
-
A.
Shilha
Shilha is a major Berber (Amazigh) language of southwestern Morocco, spoken primarily by the Shilha people in the Atlas and Anti-Atlas regions.
-
B.
Can Tho
Can Tho is a major city in southern Vietnam and the economic and cultural hub of the Mekong Delta region, known for its bustling floating markets and extensive canal network.
-
C.
Hyakutake
Hyakutake is a Japanese surname borne by several notable individuals, including military figures and other public personalities.
-
D.
Mount Lee
Mount Lee is a hill in the Hollywood Hills of Los Angeles best known as the site overlooking the iconic Hollywood Sign.
-
E.
Tien Shan
Tien Shan is a vast Central Asian mountain system spanning several countries, known for its high, glaciated peaks and role as a major source of regional rivers.
- 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: Maung Triple: [Cynthia Maung, familyName, Maung]
Generated description
Maung is a Burmese surname commonly used in Myanmar and among the Burmese diaspora.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maung Target entity description: Maung is a Burmese surname commonly used in Myanmar and among the Burmese diaspora.
-
A.
Shilha
Shilha is a major Berber (Amazigh) language of southwestern Morocco, spoken primarily by the Shilha people in the Atlas and Anti-Atlas regions.
-
B.
Can Tho
Can Tho is a major city in southern Vietnam and the economic and cultural hub of the Mekong Delta region, known for its bustling floating markets and extensive canal network.
-
C.
Hyakutake
Hyakutake is a Japanese surname borne by several notable individuals, including military figures and other public personalities.
-
D.
Mount Lee
Mount Lee is a hill in the Hollywood Hills of Los Angeles best known as the site overlooking the iconic Hollywood Sign.
-
E.
Tien Shan
Tien Shan is a vast Central Asian mountain system spanning several countries, known for its high, glaciated peaks and role as a major source of regional rivers.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d39eb3881909f435043c8697f13 |
completed | Feb. 28, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a37374e97c819090a8921d5c27d1ab |
completed | Feb. 28, 2026, 11 p.m. |
| NEDg | Description generation | batch_69a37424ca448190aeb43c7922fbd1dd |
completed | Feb. 28, 2026, 11:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3747b0bf481908b197614d9f2d04c |
completed | Feb. 28, 2026, 11:04 p.m. |
Created at: Feb. 28, 2026, 2:54 a.m.