Triple
T20440888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Qun |
E501386
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Zhang |
—
|
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: Zhang | Statement: [Zhang Qun, familyName, Zhang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhang Context triple: [Zhang Qun, familyName, Zhang]
-
A.
Zhang
chosen
Zhang is a common Chinese surname historically borne by members of the Jewish community of Kaifeng.
-
B.
Zheng Zhang
Zheng Zhang is a computer vision and deep learning researcher known for co-authoring the influential Swin Transformer architecture for visual recognition tasks.
-
C.
Zeng
Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in China.
-
D.
Zhang Ding
Zhang Ding was a prominent Chinese artist and designer best known for creating iconic national symbols of the People’s Republic of China.
-
E.
Zhao
Zhao is a common Chinese surname, historically borne by some members of the Jewish community of Kaifeng in China.
- 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_69e0b4ab3cfc8190ac9bf32e932316b1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e685f2e8888190a2e0d6b2bf6c905d |
completed | April 20, 2026, 8 p.m. |
Created at: April 16, 2026, 11:31 a.m.