Triple
T3584381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liu Shaoqi |
E75876
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Shaoqi
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
|
E371856
|
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: Shaoqi | Statement: [Liu Shaoqi, givenName, Shaoqi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shaoqi Context triple: [Liu Shaoqi, givenName, Shaoqi]
-
A.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
-
B.
Xue Yue
Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
C.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
D.
Shanshan
Shanshan was an ancient oasis kingdom in the eastern Tarim Basin, known for its role as a Silk Road crossroads and its mix of Indo-European and Chinese cultural influences.
-
E.
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."
- 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: Shaoqi Triple: [Liu Shaoqi, givenName, Shaoqi]
Generated description
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shaoqi Target entity description: Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
-
A.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
-
B.
Xue Yue
Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
C.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
D.
Shanshan
Shanshan was an ancient oasis kingdom in the eastern Tarim Basin, known for its role as a Silk Road crossroads and its mix of Indo-European and Chinese cultural influences.
-
E.
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."
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc10f9b508190bde4a4e4711dd452 |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402f7ee6481908d06db05f9c09faf |
completed | March 13, 2026, 12:28 p.m. |
| NEDg | Description generation | batch_69b403acc5e88190bc88bed8259393ba |
completed | March 13, 2026, 12:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b40a7f82ac819099c2c324ebff76f7 |
completed | March 13, 2026, 1 p.m. |
Created at: March 8, 2026, 3:21 p.m.