Triple
T14308279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hua Guofeng |
E354753
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hua |
E546083
|
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: Hua | Statement: [Hua Guofeng, familyName, Hua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hua Context triple: [Hua Guofeng, familyName, Hua]
-
A.
Hua
chosen
Hua is a Chinese given name commonly used for both males and females, often associated with meanings like "flower" or "China."
-
B.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
-
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.
Huayu
Huayu is a term used primarily in Singapore, Malaysia, and other overseas Chinese communities to refer to the standardized form of Mandarin Chinese used in education and media.
-
E.
Huating
Huating is a historical town that once served as the name and administrative center of what is now Shanghai’s Songjiang District.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b26da48190a96e2f60ace51335 |
completed | April 14, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d2e2444819090252684673ff3df |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:12 a.m.