Triple
T17749123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Story of Qiu Ju |
E443067
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Qiu Ju |
—
|
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: Qiu Ju | Statement: [The Story of Qiu Ju, mainCharacter, Qiu Ju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qiu Ju Context triple: [The Story of Qiu Ju, mainCharacter, Qiu Ju]
-
A.
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.
-
B.
Lin Sen
Lin Sen was a Chinese politician who served as the chairman of the National Government of the Republic of China during the turbulent years leading up to and including much of the Second Sino-Japanese War.
-
C.
Pai Mei
Pai Mei is a legendary, ruthless martial arts master in Quentin Tarantino’s Kill Bill saga, known for his brutal training methods and near-mythic fighting skills.
-
D.
Jiang Wu
chosen
Jiang Wu is a Chinese actor known for his roles in both mainstream and art-house films, often portraying intense and complex characters.
-
E.
Sima Kang
Sima Kang was a historical figure associated with the compilation of the Chinese chronicle Zizhi Tongjian, contributing to its editorial work.
- 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_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 10:10 a.m.