Triple
T21842997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Chen |
E539300
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Chen Chong |
—
|
NE NERFINISHED |
How this triple was built (2 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: Chen Chong | Statement: [Joan Chen, alternateName, Chen Chong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chen Chong Context triple: [Joan Chen, alternateName, Chen Chong]
-
A.
Chen Chong
chosen
Chen Chong, better known internationally as Joan Chen, is a Chinese-American actress and director acclaimed for her roles in films like "The Last Emperor" and "Twin Peaks."
-
B.
Chen He
Chen He is a popular Chinese actor and television personality best known for his comedic roles in hit sitcoms and variety shows.
-
C.
Chen Han
Chen Han is an actor known for appearing in the acclaimed family drama film "The Farewell."
-
D.
Chen Jitang
Chen Jitang was a prominent Chinese warlord and Nationalist general who controlled much of Guangdong in the 1930s and played a key role in regional politics during the Republic of China era.
-
E.
Chen Yaozu
Chen Yaozu was a Chinese military figure and graduate of the prestigious Yunnan Military Academy, known for producing many influential officers in modern Chinese history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7ad76d48190a1905cfdbe866323 |
completed | April 28, 2026, 12:27 p.m. |
Created at: April 16, 2026, 6:55 p.m.