Triple
T8158120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guan Yu |
E190504
|
entity |
| Predicate | courtesyName |
P570
|
FINISHED |
| Object |
Yunchang
Yunchang is the courtesy name of Guan Yu, the famed general of the late Eastern Han dynasty and a central heroic figure in Chinese history and the Romance of the Three Kingdoms.
|
E738203
|
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: Yunchang | Statement: [Guan Yu, courtesyName, Yunchang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yunchang Context triple: [Guan Yu, courtesyName, Yunchang]
-
A.
Ziyang
Ziyang is the art name (courtesy name) of Zhu Xi, the influential Neo-Confucian philosopher of the Southern Song dynasty.
-
B.
Ziyang
Ziyang is a city in Sichuan Province, China, located within the fertile and densely populated Chengdu Plain region.
-
C.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
D.
Guangshui
Guangshui is a county-level city in central China's Hubei province, known for its historical sites and role as a regional transportation hub.
-
E.
Hanchuan
Hanchuan is a county-level city in central China's Hubei Province, known for its location within the fertile Jianghan Plain and its role in regional agriculture and industry.
- 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: Yunchang Triple: [Guan Yu, courtesyName, Yunchang]
Generated description
Yunchang is the courtesy name of Guan Yu, the famed general of the late Eastern Han dynasty and a central heroic figure in Chinese history and the Romance of the Three Kingdoms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yunchang Target entity description: Yunchang is the courtesy name of Guan Yu, the famed general of the late Eastern Han dynasty and a central heroic figure in Chinese history and the Romance of the Three Kingdoms.
-
A.
Ziyang
Ziyang is the art name (courtesy name) of Zhu Xi, the influential Neo-Confucian philosopher of the Southern Song dynasty.
-
B.
Ziyang
Ziyang is a city in Sichuan Province, China, located within the fertile and densely populated Chengdu Plain region.
-
C.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
D.
Guangshui
Guangshui is a county-level city in central China's Hubei province, known for its historical sites and role as a regional transportation hub.
-
E.
Hanchuan
Hanchuan is a county-level city in central China's Hubei Province, known for its location within the fertile Jianghan Plain and its role in regional agriculture and industry.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44da14a481909f8d3277762b0e75 |
completed | March 31, 2026, 3:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4d66c6708190919b8c1800af2d72 |
completed | April 2, 2026, 11:05 a.m. |
| NEDg | Description generation | batch_69ce4f556a408190b404481a32b2457b |
completed | April 2, 2026, 11:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce503737a4819083ebf9f410eac826 |
completed | April 2, 2026, 11:17 a.m. |
Created at: March 30, 2026, 5:38 p.m.