Triple
T3249176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulan (1998 film) |
E68134
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
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.
|
E340819
|
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: Chi-Fu | Statement: [Mulan (1998 film), character, Chi-Fu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chi-Fu Context triple: [Mulan (1998 film), character, Chi-Fu]
-
A.
Rikichi
Rikichi is a Japanese masculine given name that can be borne by various real or fictional individuals.
-
B.
Mr. Wuf
Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
-
C.
Masaru
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
-
D.
Chun
Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
-
E.
Shinya
Shinya is a Japanese given name commonly used for males.
- 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: Chi-Fu Triple: [Mulan (1998 film), character, Chi-Fu]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chi-Fu Target entity description: 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.
-
A.
Rikichi
Rikichi is a Japanese masculine given name that can be borne by various real or fictional individuals.
-
B.
Mr. Wuf
Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
-
C.
Masaru
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
-
D.
Chun
Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
-
E.
Shinya
Shinya is a Japanese given name commonly used for males.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2776934108190ac405ba5ebd47084 |
completed | March 12, 2026, 8:20 a.m. |
| NEDg | Description generation | batch_69b27c2c16188190af03674ead3944de |
completed | March 12, 2026, 8:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b27ca63b1c8190ac6f67aef6d2c7e1 |
completed | March 12, 2026, 8:43 a.m. |
Created at: March 8, 2026, 3:09 p.m.