Triple
T5369370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao Xinyu |
E108808
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Xinyu |
E187720
|
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: Xinyu | Statement: [Mao Xinyu, givenName, Xinyu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinyu Context triple: [Mao Xinyu, givenName, Xinyu]
-
A.
Xinyu
chosen
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
-
B.
Xinyi
Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
-
C.
Yuxiang
Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
-
D.
Jinyang
Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
-
E.
Yuanxin
Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd86873e0c8190bf5ecede2cc2bd8b |
completed | March 20, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3a94acc48190a4c0ea39c6b8a405 |
completed | March 22, 2026, 12:40 a.m. |
Created at: March 20, 2026, 2:02 p.m.