Triple
T19383366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Fang (2018 film) |
E484867
|
entity |
| Predicate | voiceCastMember |
P9616
|
FINISHED |
| Object |
Tommy Lee Baïk
Tommy Lee Baïk is a voice actor known for his role in the 2018 animated film adaptation of "White Fang."
|
E1373208
|
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: Tommy Lee Baïk | Statement: [White Fang (2018 film), voiceCastMember, Tommy Lee Baïk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tommy Lee Baïk Context triple: [White Fang (2018 film), voiceCastMember, Tommy Lee Baïk]
-
A.
Johnny Chiang
Johnny Chiang is a Taiwanese politician who has served as a prominent leader within the Kuomintang (KMT) party and as a legislator in Taiwan’s Legislative Yuan.
-
B.
Tony Lee
Tony Lee is known as the son of longtime U.S. Representative Barbara Lee, a prominent Democratic politician from California.
-
C.
Tony Lee
Tony Lee is an actor known for his role in the Australian drama film "Romper Stomper."
-
D.
Jimmy Lei Ba
Jimmy Lei Ba is a machine learning researcher known for influential contributions to deep learning optimization and normalization techniques, including the development of Layer Normalization.
-
E.
Ming Lee
Ming Lee is the strict yet loving mother of protagonist Meilin in Pixar's animated film "Turning Red," whose own emotional struggles and family legacy drive much of the story's conflict and heart.
- 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: Tommy Lee Baïk Triple: [White Fang (2018 film), voiceCastMember, Tommy Lee Baïk]
Generated description
Tommy Lee Baïk is a voice actor known for his role in the 2018 animated film adaptation of "White Fang."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tommy Lee Baïk Target entity description: Tommy Lee Baïk is a voice actor known for his role in the 2018 animated film adaptation of "White Fang."
-
A.
Johnny Chiang
Johnny Chiang is a Taiwanese politician who has served as a prominent leader within the Kuomintang (KMT) party and as a legislator in Taiwan’s Legislative Yuan.
-
B.
Tony Lee
Tony Lee is known as the son of longtime U.S. Representative Barbara Lee, a prominent Democratic politician from California.
-
C.
Tony Lee
Tony Lee is an actor known for his role in the Australian drama film "Romper Stomper."
-
D.
Jimmy Lei Ba
Jimmy Lei Ba is a machine learning researcher known for influential contributions to deep learning optimization and normalization techniques, including the development of Layer Normalization.
-
E.
Ming Lee
Ming Lee is the strict yet loving mother of protagonist Meilin in Pixar's animated film "Turning Red," whose own emotional struggles and family legacy drive much of the story's conflict and heart.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a614cf88190b561eafaa350ce19 |
completed | April 20, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a072b7ec8ac8190b9330f239e44f795 |
completed | May 15, 2026, 2:19 p.m. |
| NEDg | Description generation | batch_6a072de198fc8190838ce30942cc46df |
completed | May 15, 2026, 2:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a072e5e62a88190af09d9911a6f1413 |
completed | May 15, 2026, 2:31 p.m. |
Created at: April 10, 2026, 1:35 p.m.