Triple
T11985620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Hiroyuki Liao |
E285269
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Liao
Liao is a surname of Chinese origin borne by various notable individuals across fields such as acting, politics, and academia.
|
E958343
|
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: Liao | Statement: [James Hiroyuki Liao, familyName, Liao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liao Context triple: [James Hiroyuki Liao, familyName, Liao]
-
A.
Luoyi
Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
-
B.
Ronglu
Ronglu was a high-ranking Qing dynasty general and statesman who played a key role in military and political affairs during the late imperial period, including the Boxer Rebellion.
-
C.
Liang
Liang is a common Chinese surname borne by numerous historical figures, scholars, and public personalities across the Chinese-speaking world.
-
D.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
-
E.
Yuanzhong
Yuanzhong was the courtesy name of Cao Rui, the second emperor of the state of Cao Wei during China’s Three Kingdoms period.
- 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: Liao Triple: [James Hiroyuki Liao, familyName, Liao]
Generated description
Liao is a surname of Chinese origin borne by various notable individuals across fields such as acting, politics, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liao Target entity description: Liao is a surname of Chinese origin borne by various notable individuals across fields such as acting, politics, and academia.
-
A.
Luoyi
Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
-
B.
Ronglu
Ronglu was a high-ranking Qing dynasty general and statesman who played a key role in military and political affairs during the late imperial period, including the Boxer Rebellion.
-
C.
Liang
Liang is a common Chinese surname borne by numerous historical figures, scholars, and public personalities across the Chinese-speaking world.
-
D.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
-
E.
Yuanzhong
Yuanzhong was the courtesy name of Cao Rui, the second emperor of the state of Cao Wei during China’s Three Kingdoms period.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47237c23081909044388ff5dc73b3 |
completed | May 1, 2026, 9:28 a.m. |
| NEDg | Description generation | batch_69f47b7c5af08190ab0bff1232530a0c |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47dd51e648190bddd41766221e22d |
completed | May 1, 2026, 10:17 a.m. |
Created at: April 8, 2026, 9:46 p.m.