Triple
T14983243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wang Guangmei |
E373633
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Guangmei
Guangmei is a Chinese given name, notably borne by Wang Guangmei, the influential political figure and wife of former Chinese president Liu Shaoqi.
|
E1130458
|
NE FINISHED |
How this triple was built (4 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: Guangmei | Statement: [Wang Guangmei, givenName, Guangmei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guangmei Context triple: [Wang Guangmei, givenName, Guangmei]
-
A.
Xiangmei
Xiangmei is the Chinese given name of Anna Chennault, a prominent Chinese-American journalist, author, and influential political figure in mid-20th-century U.S.-China relations.
-
B.
Xuefei
Xuefei is the Chinese given name of Ha Jin, the acclaimed Chinese-American novelist and poet known for works such as "Waiting."
-
C.
Juyi
Juyi is the given name of Bai Juyi, a renowned Tang dynasty Chinese poet celebrated for his accessible style and social commentary.
-
D.
Weihui
Weihui is a county-level city in northern Henan Province, China, administered by the prefecture-level city of Xinxiang.
-
E.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Guangmei Triple: [Wang Guangmei, givenName, Guangmei]
Generated description
Guangmei is a Chinese given name, notably borne by Wang Guangmei, the influential political figure and wife of former Chinese president Liu Shaoqi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guangmei Target entity description: Guangmei is a Chinese given name, notably borne by Wang Guangmei, the influential political figure and wife of former Chinese president Liu Shaoqi.
-
A.
Xiangmei
Xiangmei is the Chinese given name of Anna Chennault, a prominent Chinese-American journalist, author, and influential political figure in mid-20th-century U.S.-China relations.
-
B.
Xuefei
Xuefei is the Chinese given name of Ha Jin, the acclaimed Chinese-American novelist and poet known for works such as "Waiting."
-
C.
Juyi
Juyi is the given name of Bai Juyi, a renowned Tang dynasty Chinese poet celebrated for his accessible style and social commentary.
-
D.
Weihui
Weihui is a county-level city in northern Henan Province, China, administered by the prefecture-level city of Xinxiang.
-
E.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
- F. None of above. chosen
Provenance (5 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fe42a081909308f788fdf024d5 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bf136e88190b3d812f50233c640 |
completed | May 9, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69fe908c25c88190be07a8e12a5cd70b |
completed | May 9, 2026, 1:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9136938081908290c0dfbf140c63 |
completed | May 9, 2026, 1:43 a.m. |
Created at: April 10, 2026, 2:52 a.m.