Triple
T17749022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ju Dou |
E443065
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Ju Dou |
—
|
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: Ju Dou | Statement: [Ju Dou, title, Ju Dou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ju Dou Context triple: [Ju Dou, title, Ju Dou]
-
A.
Ju Dou
chosen
Ju Dou is a 1990 Chinese drama film, co-directed by Zhang Yimou, renowned for its vivid cinematography and its tragic story of forbidden love and oppression in rural China.
-
B.
Cheng Tai Shen
Cheng Tai Shen is an actor known for his role in the critically acclaimed Mexican drama film "Biutiful."
-
C.
Kwai Tsing
Kwai Tsing is an urban district in Hong Kong known for its major container port facilities and mixed industrial-residential areas.
-
D.
Xie Feng
Xie Feng is a Chinese diplomat who serves as the People's Republic of China’s ambassador to the United States, playing a key role in managing Sino–U.S. relations.
-
E.
Su Zhu
Su Zhu is the birth name of Hua Guofeng, the Chinese Communist leader who briefly succeeded Mao Zedong as paramount leader of China in the late 1970s.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad46a50819089c87f74efe3c7ca |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:10 a.m.