Triple
T3394894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Yuanhong |
E71504
|
entity |
| Predicate | headOfGovernment |
P307
|
FINISHED |
| Object |
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
|
E378875
|
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: Li Jingxi | Statement: [Li Yuanhong, headOfGovernment, Li Jingxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Li Jingxi Context triple: [Li Yuanhong, headOfGovernment, Li Jingxi]
-
A.
Li Xiuwen
Li Xiuwen was the wife of Chinese military leader and revolutionary Ye Ting.
-
B.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
C.
Jing Tian
Jing Tian is a Chinese actress known for her roles in both Chinese cinema and Hollywood blockbusters such as "Pacific Rim: Uprising" and "The Great Wall."
-
D.
Lin Yurong
Lin Yurong is the original birth name of Lin Biao, a prominent Chinese Communist military leader and key figure in the Chinese Civil War and early People’s Republic of China.
-
E.
Lu Lingzi
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
- 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: Li Jingxi Triple: [Li Yuanhong, headOfGovernment, Li Jingxi]
Generated description
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Li Jingxi Target entity description: Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
A.
Li Xiuwen
Li Xiuwen was the wife of Chinese military leader and revolutionary Ye Ting.
-
B.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
C.
Jing Tian
Jing Tian is a Chinese actress known for her roles in both Chinese cinema and Hollywood blockbusters such as "Pacific Rim: Uprising" and "The Great Wall."
-
D.
Lin Yurong
Lin Yurong is the original birth name of Lin Biao, a prominent Chinese Communist military leader and key figure in the Chinese Civil War and early People’s Republic of China.
-
E.
Lu Lingzi
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb85487088190b8a4ec546ff8a461 |
completed | March 8, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c36c12008190b21c47091a4e2ca6 |
completed | March 14, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69b4c4215ba481908d9d8eeb24ea298b |
completed | March 14, 2026, 2:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c494ad80819084d6aa10fe62a63b |
completed | March 14, 2026, 2:14 a.m. |
Created at: March 8, 2026, 3:14 p.m.