Triple
T21502344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justin Lin |
E530506
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Lin Yipeng |
—
|
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: Lin Yipeng | Statement: [Justin Lin, birthName, Lin Yipeng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lin Yipeng Context triple: [Justin Lin, birthName, Lin Yipeng]
-
A.
Lin Yipeng
chosen
Lin Yipeng is the birth name of Justin Lin, a Taiwanese-American film director best known for his work on the Fast & Furious franchise.
-
B.
Jin Yunpeng
Jin Yunpeng was an early 20th-century Chinese military and political figure who twice served as premier during the turbulent warlord era of the Republic of China.
-
C.
Li Jinglong
Li Jinglong was a Ming dynasty general best known for his unsuccessful leadership of imperial forces against Zhu Di during the Jingnan campaign.
-
D.
Li Jingliang
Li Jingliang is a Chinese mixed martial artist and UFC welterweight known for his aggressive striking style and knockout power.
-
E.
Jun Yu
Jun Yu is an actor known for his role in Disney's live-action adaptation of "Mulan" (2020).
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5d209881908754eb07a47e478a |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:24 p.m.