Triple
T17069895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulan (2020 film) |
E414187
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Jun Yu
Jun Yu is an actor known for his role in Disney's live-action adaptation of "Mulan" (2020).
|
E1251934
|
NE FINISHED |
How this triple was built (4 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: Jun Yu | Statement: [Mulan (2020 film), castMember, Jun Yu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jun Yu Context triple: [Mulan (2020 film), castMember, Jun Yu]
-
A.
Xiong Yi
Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
-
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.
Yao Yecheng
Yao Yecheng was the adoptive mother of Chiang Wei-kuo, the son of Chinese Nationalist leader Chiang Kai-shek.
-
D.
Li Jiajun
Li Jiajun is a Chinese short track speed skater who was one of the sport’s leading competitors in the late 1990s and early 2000s, winning multiple Olympic and World Championship medals.
-
E.
Lin Yipeng
Lin Yipeng is the birth name of Justin Lin, a Taiwanese-American film director best known for his work on the Fast & Furious franchise.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jun Yu Triple: [Mulan (2020 film), castMember, Jun Yu]
Generated description
Jun Yu is an actor known for his role in Disney's live-action adaptation of "Mulan" (2020).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jun Yu Target entity description: Jun Yu is an actor known for his role in Disney's live-action adaptation of "Mulan" (2020).
-
A.
Xiong Yi
Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
-
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.
Yao Yecheng
Yao Yecheng was the adoptive mother of Chiang Wei-kuo, the son of Chinese Nationalist leader Chiang Kai-shek.
-
D.
Li Jiajun
Li Jiajun is a Chinese short track speed skater who was one of the sport’s leading competitors in the late 1990s and early 2000s, winning multiple Olympic and World Championship medals.
-
E.
Lin Yipeng
Lin Yipeng is the birth name of Justin Lin, a Taiwanese-American film director best known for his work on the Fast & Furious franchise.
- F. None of above. chosen
Provenance (5 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbfb1f08190807301ff6e573cf5 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014140722481909f976e32597a873d |
completed | May 11, 2026, 2:38 a.m. |
| NEDg | Description generation | batch_6a0141cadb6c8190b2832e12fd431b0b |
completed | May 11, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a014264ff8881909722c262c3f85e1f |
completed | May 11, 2026, 2:43 a.m. |
Created at: April 10, 2026, 5:34 a.m.