Triple
T9918554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Wu of Han |
E185930
|
entity |
| Predicate | general |
P68492
|
FINISHED |
| Object |
Li Ling
Li Ling was a Han dynasty military general best known for his ill-fated campaign against the Xiongnu and subsequent controversial surrender that sparked political turmoil in the Han court.
|
E832651
|
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 Ling | Statement: [Emperor Wu of Han, general, Li Ling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Li Ling Context triple: [Emperor Wu of Han, general, Li Ling]
-
A.
Lu Lingzi
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
-
B.
Yao Ling
Yao Ling is known as the former spouse of Ren Zhengfei, the founder of Chinese telecommunications giant Huawei.
-
C.
Lu Lingjia
Lu Lingjia is a Chinese individual known primarily as a relative of Lu Lingzi, one of the victims of the 2013 Boston Marathon bombing.
-
D.
Liu Shu
Liu Shu was a Chinese scholar who contributed as an editor to the compilation of the historical chronicle Zizhi Tongjian.
-
E.
Liu Qin
Liu Qin was a prince of the Eastern Han dynasty, known primarily as a son of Emperor Guangwu of Han.
- 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 Ling Triple: [Emperor Wu of Han, general, Li Ling]
Generated description
Li Ling was a Han dynasty military general best known for his ill-fated campaign against the Xiongnu and subsequent controversial surrender that sparked political turmoil in the Han court.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Li Ling Target entity description: Li Ling was a Han dynasty military general best known for his ill-fated campaign against the Xiongnu and subsequent controversial surrender that sparked political turmoil in the Han court.
-
A.
Lu Lingzi
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
-
B.
Yao Ling
Yao Ling is known as the former spouse of Ren Zhengfei, the founder of Chinese telecommunications giant Huawei.
-
C.
Lu Lingjia
Lu Lingjia is a Chinese individual known primarily as a relative of Lu Lingzi, one of the victims of the 2013 Boston Marathon bombing.
-
D.
Liu Shu
Liu Shu was a Chinese scholar who contributed as an editor to the compilation of the historical chronicle Zizhi Tongjian.
-
E.
Liu Qin
Liu Qin was a prince of the Eastern Han dynasty, known primarily as a son of Emperor Guangwu of Han.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb5685a908190ab3e55b9bf9613f6 |
completed | April 2, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d2e676c81909e4eed258ecdf053 |
completed | April 5, 2026, 10:45 a.m. |
| NEDg | Description generation | batch_69d24135c0b88190ad018858b99e0bde |
completed | April 5, 2026, 11:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d241ca07b481908a2852ed15ed5cf2 |
completed | April 5, 2026, 11:04 a.m. |
Created at: March 30, 2026, 8:42 p.m.