Triple
T9192031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoa people |
E220613
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Hoa |
E220613
|
NE FINISHED |
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: Hoa | Statement: [Hoa people, nativeName, Hoa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoa Context triple: [Hoa people, nativeName, Hoa]
-
A.
Hoa
chosen
The Hoa are an ethnic Chinese minority community in Vietnam, particularly concentrated in the Mekong Delta and major urban centers.
-
B.
Bunga
Bunga is a brave and energetic honey badger who serves as the comedic yet fearless member of the Lion Guard in the Disney Junior series.
-
C.
Hạua
Hạua is a small outlying islet associated with the Polynesian island of Rotuma in the South Pacific Ocean.
-
D.
Hua
Hua is a Chinese given name commonly used for both males and females, often associated with meanings like "flower" or "China."
-
E.
Hana
Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5c077b4819086c74e91ee4bd75e |
completed | April 1, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c2bb2c481909db8c223aececf37 |
completed | April 4, 2026, 12:32 a.m. |
Created at: March 30, 2026, 7:24 p.m.