Triple
T1430326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao Fumei |
E30428
|
entity |
| Predicate | placeOfResidence |
P75
|
FINISHED |
| Object |
Fenghua
Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
|
E172352
|
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: Fenghua | Statement: [Mao Fumei, placeOfResidence, Fenghua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fenghua Context triple: [Mao Fumei, placeOfResidence, Fenghua]
-
A.
Haining
Haining is a county-level city in Zhejiang Province, China, known for its dramatic tidal bore on the Qiantang River and its textile industry.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Taizhou
Taizhou is a prefecture-level city in eastern China known for its historical heritage and location along the Yangtze River in Jiangsu province.
-
D.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
E.
Wuxi
Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
- 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: Fenghua Triple: [Mao Fumei, placeOfResidence, Fenghua]
Generated description
Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fenghua Target entity description: Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
-
A.
Haining
Haining is a county-level city in Zhejiang Province, China, known for its dramatic tidal bore on the Qiantang River and its textile industry.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Taizhou
Taizhou is a prefecture-level city in eastern China known for its historical heritage and location along the Yangtze River in Jiangsu province.
-
D.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
E.
Wuxi
Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4db2d7481908d241593d0e17d83 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad232534f48190b1392c2fba119b7c |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad244de35881908f37bf10fa9cf1c9 |
completed | March 8, 2026, 7:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad24aea1988190af6e847cc1842520 |
completed | March 8, 2026, 7:26 a.m. |
Created at: March 1, 2026, 8 p.m.