Triple
T7714543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kung Fu Panda 2 |
E174847
|
entity |
| Predicate | characterFeatured |
P12208
|
FINISHED |
| Object |
Shifu
Shifu is the wise and disciplined red panda kung fu master who trains Po and the Furious Five in the Kung Fu Panda film series.
|
E683353
|
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: Shifu | Statement: [Kung Fu Panda 2, characterFeatured, Shifu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shifu Context triple: [Kung Fu Panda 2, characterFeatured, Shifu]
-
A.
Tai Lung
Tai Lung is the powerful snow leopard martial artist who serves as the main antagonist in the first Kung Fu Panda film.
-
B.
Chi-Fu
Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
-
C.
Panda Po
"Panda Po" is a musical track from the score of the animated film "Kung Fu Panda" (2008), composed to reflect the character Po's personality and journey.
-
D.
Ka-chiu
Ka-chiu is the given name of John Lee Ka-chiu, the Chief Executive of Hong Kong and a former security official.
-
E.
Mr. Wuf
Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
- 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: Shifu Triple: [Kung Fu Panda 2, characterFeatured, Shifu]
Generated description
Shifu is the wise and disciplined red panda kung fu master who trains Po and the Furious Five in the Kung Fu Panda film series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shifu Target entity description: Shifu is the wise and disciplined red panda kung fu master who trains Po and the Furious Five in the Kung Fu Panda film series.
-
A.
Tai Lung
Tai Lung is the powerful snow leopard martial artist who serves as the main antagonist in the first Kung Fu Panda film.
-
B.
Chi-Fu
Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
-
C.
Panda Po
"Panda Po" is a musical track from the score of the animated film "Kung Fu Panda" (2008), composed to reflect the character Po's personality and journey.
-
D.
Ka-chiu
Ka-chiu is the given name of John Lee Ka-chiu, the Chief Executive of Hong Kong and a former security official.
-
E.
Mr. Wuf
Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ca8f048190a6ea27b8cee2f93e |
completed | March 27, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8acd5e32c8190869834b21aeae8a7 |
completed | March 29, 2026, 4:38 a.m. |
| NEDg | Description generation | batch_69c8ae0383688190be1dbd27262fe717 |
completed | March 29, 2026, 4:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8ae85027c81908a7871ebcb0d27bd |
completed | March 29, 2026, 4:45 a.m. |
Created at: March 27, 2026, 4:04 p.m.