Triple
T15842576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan Grand Prix |
E384133
|
entity |
| Predicate | engineSupplier |
P17328
|
FINISHED |
| Object |
Mugen-Honda
Mugen-Honda was a racing engine partnership between Mugen Motorsports and Honda that supplied competitive Formula One power units in the 1990s.
|
E1180601
|
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: Mugen-Honda | Statement: [Jordan Grand Prix, engineSupplier, Mugen-Honda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mugen-Honda Context triple: [Jordan Grand Prix, engineSupplier, Mugen-Honda]
-
A.
Suzuki
Suzuki is a common Japanese surname borne by many notable individuals across sports, entertainment, and other fields.
-
B.
Honda
Honda is a major Japanese automobile and motorcycle manufacturer known for its reliable, fuel-efficient vehicles and global market presence.
-
C.
Honda
Honda is a historic Colombian river port city on the Magdalena River, known for its colonial architecture and numerous bridges.
-
D.
Suzuki Motor Corporation
Suzuki Motor Corporation is a Japanese multinational automaker best known for its compact cars, motorcycles, and all-terrain vehicles sold worldwide.
-
E.
Kawasaki
Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
- 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: Mugen-Honda Triple: [Jordan Grand Prix, engineSupplier, Mugen-Honda]
Generated description
Mugen-Honda was a racing engine partnership between Mugen Motorsports and Honda that supplied competitive Formula One power units in the 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mugen-Honda Target entity description: Mugen-Honda was a racing engine partnership between Mugen Motorsports and Honda that supplied competitive Formula One power units in the 1990s.
-
A.
Suzuki
Suzuki is a common Japanese surname borne by many notable individuals across sports, entertainment, and other fields.
-
B.
Honda
Honda is a major Japanese automobile and motorcycle manufacturer known for its reliable, fuel-efficient vehicles and global market presence.
-
C.
Honda
Honda is a historic Colombian river port city on the Magdalena River, known for its colonial architecture and numerous bridges.
-
D.
Suzuki Motor Corporation
Suzuki Motor Corporation is a Japanese multinational automaker best known for its compact cars, motorcycles, and all-terrain vehicles sold worldwide.
-
E.
Kawasaki
Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa13eab4881908794104508ba53af |
completed | May 9, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69ffa527af048190b1f87d85e50bf254 |
completed | May 9, 2026, 9:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffa5df00e481909e203e78940395ed |
completed | May 9, 2026, 9:23 p.m. |
Created at: April 10, 2026, 4:50 a.m.