Triple
T3785229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speed Racer (2008 film) |
E85513
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Mom Racer
Mom Racer is the caring and supportive mother of the protagonist in the 2008 live-action film adaptation of the classic anime Speed Racer.
|
E387860
|
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: Mom Racer | Statement: [Speed Racer (2008 film), character, Mom Racer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mom Racer Context triple: [Speed Racer (2008 film), character, Mom Racer]
-
A.
Racers
The Racers are the athletic teams representing Murray State University in intercollegiate sports.
-
B.
RC Racer
RC Racer is a high-speed, U-shaped shuttle roller coaster themed after the remote-control car from Pixar's Toy Story films.
-
C.
Wacky Races
Wacky Races is an animated comedy television series featuring a cast of eccentric racers and outrageous vehicles competing in chaotic, slapstick-filled car races.
-
D.
Speed Racer
Speed Racer is a 2008 live-action film adaptation of the classic Japanese anime and manga series, known for its hyper-stylized visuals and high-octane racing sequences.
-
E.
Derby Racer
Derby Racer is a classic wooden racing carousel-style amusement ride known for its high-speed, side-by-side galloping horses.
- 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: Mom Racer Triple: [Speed Racer (2008 film), character, Mom Racer]
Generated description
Mom Racer is the caring and supportive mother of the protagonist in the 2008 live-action film adaptation of the classic anime Speed Racer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mom Racer Target entity description: Mom Racer is the caring and supportive mother of the protagonist in the 2008 live-action film adaptation of the classic anime Speed Racer.
-
A.
Racers
The Racers are the athletic teams representing Murray State University in intercollegiate sports.
-
B.
RC Racer
RC Racer is a high-speed, U-shaped shuttle roller coaster themed after the remote-control car from Pixar's Toy Story films.
-
C.
Wacky Races
Wacky Races is an animated comedy television series featuring a cast of eccentric racers and outrageous vehicles competing in chaotic, slapstick-filled car races.
-
D.
Speed Racer
Speed Racer is a 2008 live-action film adaptation of the classic Japanese anime and manga series, known for its hyper-stylized visuals and high-octane racing sequences.
-
E.
Derby Racer
Derby Racer is a classic wooden racing carousel-style amusement ride known for its high-speed, side-by-side galloping horses.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3dd80f08190a1704521a764e22c |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f04a35448190a57f431ef703b1e1 |
completed | March 14, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69b4f159d7e88190a76d51378ba141d3 |
completed | March 14, 2026, 5:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4f220f9388190b2c3615f713f01f2 |
completed | March 14, 2026, 5:29 a.m. |
Created at: March 9, 2026, 3:13 p.m.