Triple
T11528155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce Lee |
E273351
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Jun-fan
Jun-fan is the Chinese given name of Bruce Lee, the legendary martial artist, actor, and cultural icon.
|
E929526
|
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-fan | Statement: [Bruce Lee, givenName, Jun-fan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jun-fan Context triple: [Bruce Lee, givenName, Jun-fan]
-
A.
Shan Yu
Shan Yu is the ruthless and intimidating leader of the Huns who serves as the primary antagonist in Disney’s animated film "Mulan."
-
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.
Young Chang
Young Chang is a South Korean musical instrument manufacturer best known for producing pianos and owning the Kurzweil brand of digital keyboards and synthesizers.
-
D.
Fan Ju
Fan Ju was an influential Warring States–period strategist and statesman who helped transform the Qin state into a dominant power through his diplomatic and political reforms.
-
E.
Shu Chien
Shu Chien is a renowned Chinese-American physiologist and bioengineer recognized for pioneering contributions to cardiovascular biomechanics and microcirculation research.
- 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-fan Triple: [Bruce Lee, givenName, Jun-fan]
Generated description
Jun-fan is the Chinese given name of Bruce Lee, the legendary martial artist, actor, and cultural icon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jun-fan Target entity description: Jun-fan is the Chinese given name of Bruce Lee, the legendary martial artist, actor, and cultural icon.
-
A.
Shan Yu
Shan Yu is the ruthless and intimidating leader of the Huns who serves as the primary antagonist in Disney’s animated film "Mulan."
-
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.
Young Chang
Young Chang is a South Korean musical instrument manufacturer best known for producing pianos and owning the Kurzweil brand of digital keyboards and synthesizers.
-
D.
Fan Ju
Fan Ju was an influential Warring States–period strategist and statesman who helped transform the Qin state into a dominant power through his diplomatic and political reforms.
-
E.
Shu Chien
Shu Chien is a renowned Chinese-American physiologist and bioengineer recognized for pioneering contributions to cardiovascular biomechanics and microcirculation research.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d883972b10819093bd09cf8406671c |
completed | April 10, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6256e3130819095a93c8d1891b078 |
completed | April 20, 2026, 1:09 p.m. |
| NEDg | Description generation | batch_69e62cf664888190869d0d10c39d5e4a |
completed | April 20, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e66327b000819083f36c3beb969849 |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 8, 2026, 9:37 p.m.