Triple
T23002236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polar (2019 film) |
E572664
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Fei Ren |
—
|
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: Fei Ren | Statement: [Polar (2019 film), starring, Fei Ren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fei Ren Context triple: [Polar (2019 film), starring, Fei Ren]
-
A.
Fei Ren
chosen
Fei Ren is an actor best known for playing a leading role in the film "Polar."
-
B.
Xie Fei
Xie Fei was a Chinese revolutionary and political figure best known as the wife of former PRC President Liu Shaoqi.
-
C.
Tang Fei
Tang Fei is a Taiwanese military general and politician who briefly served as Premier of the Republic of China (Taiwan) in 2000 during the early presidency of Chen Shui-bian.
-
D.
Hui Fei
Hui Fei is a strong-willed and enigmatic courtesan who plays a pivotal role in the 1932 film "Shanghai Express."
-
E.
Fei Yi
Fei Yi was a prominent statesman and regent of the Shu Han kingdom during China’s Three Kingdoms period, known for his diplomatic skill and capable governance.
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18353d05481909abacb48a14ef21e |
completed | April 29, 2026, 4:04 a.m. |
Created at: April 17, 2026, 3:50 p.m.