Triple
T15382650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 宮本 茂 |
E367840
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | F-ZERO |
E367842
|
NE FINISHED |
How this triple was built (2 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: F-ZERO | Statement: [宮本 茂, notableWork, F-ZERO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: F-ZERO Context triple: [宮本 茂, notableWork, F-ZERO]
-
A.
F-Zero
chosen
F-Zero is a high-speed futuristic racing video game series by Nintendo, known for its challenging gameplay, hovercraft vehicles, and influential role in the evolution of racing games.
-
B.
Kart
Kart refers to a member or native of the Kart dynasty of Herat, a medieval ruling family in the region of present-day western Afghanistan.
-
C.
Racers
The Racers are the athletic teams representing Murray State University in intercollegiate sports.
-
D.
Racers
Racers was a professional ice hockey team based in Indianapolis that competed in the World Hockey Association during the 1970s.
-
E.
Gran Turismo
Gran Turismo is a long-running and highly realistic racing simulation video game series known for its extensive car roster and meticulous attention to driving physics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b5bc43c81908ffdb7819e3660d9 |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:19 a.m.