Triple
T8021094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Shizhen |
E186742
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Shizhen
Shizhen is the given name of Li Shizhen, the renowned Ming dynasty physician and naturalist best known for compiling the monumental Chinese medical text "Compendium of Materia Medica."
|
E713524
|
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: Shizhen | Statement: [Li Shizhen, givenName, Shizhen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shizhen Context triple: [Li Shizhen, givenName, Shizhen]
-
A.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
-
B.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
-
C.
Shen
Shen is a Chinese surname historically borne by notable figures such as the Song dynasty polymath Shen Kuo.
-
D.
Shiqi
Shiqi was a historical administrative and commercial center that served as the capital of Xiangshan County in Guangdong during the Qing Empire.
-
E.
Yüeh-chih
Yüeh-chih were an ancient Indo-European nomadic people of Central Asia who played a key role in the formation of the Kushan Empire and the cultural exchanges along the Silk Road.
- 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: Shizhen Triple: [Li Shizhen, givenName, Shizhen]
Generated description
Shizhen is the given name of Li Shizhen, the renowned Ming dynasty physician and naturalist best known for compiling the monumental Chinese medical text "Compendium of Materia Medica."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shizhen Target entity description: Shizhen is the given name of Li Shizhen, the renowned Ming dynasty physician and naturalist best known for compiling the monumental Chinese medical text "Compendium of Materia Medica."
-
A.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
-
B.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
-
C.
Shen
Shen is a Chinese surname historically borne by notable figures such as the Song dynasty polymath Shen Kuo.
-
D.
Shiqi
Shiqi was a historical administrative and commercial center that served as the capital of Xiangshan County in Guangdong during the Qing Empire.
-
E.
Yüeh-chih
Yüeh-chih were an ancient Indo-European nomadic people of Central Asia who played a key role in the formation of the Kushan Empire and the cultural exchanges along the Silk Road.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8d90488190b57d1e748e272061 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc93b18a6c81908a3a4bc25552d97b |
completed | April 1, 2026, 3:40 a.m. |
| NEDg | Description generation | batch_69cc9605b8248190a621ea934c58913d |
completed | April 1, 2026, 3:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc96fa03d881909a1eeed6af9a3149 |
completed | April 1, 2026, 3:54 a.m. |
Created at: March 30, 2026, 5:20 p.m.