Triple
T19328958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Hoan |
E483434
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hoan |
—
|
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: Hoan | Statement: [Daniel Hoan, familyName, Hoan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoan Context triple: [Daniel Hoan, familyName, Hoan]
-
A.
Hoan
chosen
Hoan is a surname most notably associated with Daniel Hoan, a long-serving Socialist mayor of Milwaukee in the early 20th century.
-
B.
Hoan-ya
Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
-
C.
Henao
Henao is a Spanish-language surname most notably associated with Maria Victoria Henao, the widow of Colombian drug lord Pablo Escobar.
-
D.
Huan
Huan is a given name most notably associated with the contemporary Chinese artist Zhang Huan, known for his performance and conceptual art.
-
E.
Hoang
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.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6163ffddc81909e9cb13e780f1f18 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 10, 2026, 1:33 p.m.