Triple
T15992164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pops Racer |
E387859
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object |
Mach GoGoGo
Mach GoGoGo is a classic 1960s Japanese anime and manga series about a young race car driver and his high-tech car, internationally known as Speed Racer.
|
E1187305
|
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: Mach GoGoGo | Statement: [Pops Racer, appearsIn, Mach GoGoGo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mach GoGoGo Context triple: [Pops Racer, appearsIn, Mach GoGoGo]
-
A.
Go Go
Go Go is a tough, speed-obsessed engineering student and superheroine from Disney's Big Hero 6.
-
B.
Love a Go Go
"Love a Go Go" is a Motown song best known for being performed by Stevie Wonder during his classic 1960s period.
-
C.
Going to a Go-Go
"Going to a Go-Go" is a 1965 Motown hit by Smokey Robinson & the Miracles, celebrated as a classic upbeat soul dance track.
-
D.
Touch and Go
Touch and Go is a track from the album "Barking at Airplanes" by American singer-songwriter Kim Carnes.
-
E.
Go Goo Go
"Go Goo Go" is a fast-paced episode of the animated series Foster's Home for Imaginary Friends that introduces Goo, an overly imaginative girl who creates countless imaginary friends, causing chaos at the foster home.
- 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: Mach GoGoGo Triple: [Pops Racer, appearsIn, Mach GoGoGo]
Generated description
Mach GoGoGo is a classic 1960s Japanese anime and manga series about a young race car driver and his high-tech car, internationally known as Speed Racer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mach GoGoGo Target entity description: Mach GoGoGo is a classic 1960s Japanese anime and manga series about a young race car driver and his high-tech car, internationally known as Speed Racer.
-
A.
Go Go
Go Go is a tough, speed-obsessed engineering student and superheroine from Disney's Big Hero 6.
-
B.
Love a Go Go
"Love a Go Go" is a Motown song best known for being performed by Stevie Wonder during his classic 1960s period.
-
C.
Going to a Go-Go
"Going to a Go-Go" is a 1965 Motown hit by Smokey Robinson & the Miracles, celebrated as a classic upbeat soul dance track.
-
D.
Touch and Go
Touch and Go is a track from the album "Barking at Airplanes" by American singer-songwriter Kim Carnes.
-
E.
Go Goo Go
"Go Goo Go" is a fast-paced episode of the animated series Foster's Home for Imaginary Friends that introduces Goo, an overly imaginative girl who creates countless imaginary friends, causing chaos at the foster home.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157844ed881908b42bfc1bb740d4e |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3d3ef2881909213ff608192f1ef |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc47bce748190a651fff307aad88d |
completed | May 9, 2026, 11:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc4e14e1881909210a78426546e88 |
completed | May 9, 2026, 11:36 p.m. |
Created at: April 10, 2026, 4:54 a.m.