Triple
T23411392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwang |
E560077
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Hoang |
—
|
NE NERFINISHED |
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: Hoang | Statement: [Hwang, hasVariant, Hoang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoang Context triple: [Hwang, hasVariant, Hoang]
-
A.
Hoang
chosen
Hoang is a Vietnamese given name and surname, often romanized from the Chinese surname Huang and widely used in Vietnam and among the Vietnamese diaspora.
-
B.
Hoan
Hoan is a surname most notably associated with Daniel Hoan, a long-serving Socialist mayor of Milwaukee in the early 20th century.
-
C.
Huan
Huan is a given name most notably associated with the contemporary Chinese artist Zhang Huan, known for his performance and conceptual art.
-
D.
Hien
Hien is the Japanese nickname for the World War II-era Kawasaki Ki-61 fighter aircraft, known for its inline engine and distinctive performance compared to other Japanese fighters.
-
E.
Huandoy
Huandoy is a prominent, glaciated mountain massif in Peru’s Cordillera Blanca, known for its multiple sharp summits and challenging climbing routes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a51183bc8190bd4860607b26b4b2 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:38 p.m.