Triple
T20187215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Kart Arcade GP |
E492893
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Namco |
—
|
NE NERFINISHED |
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: Namco | Statement: [Mario Kart Arcade GP, developer, Namco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namco Context triple: [Mario Kart Arcade GP, developer, Namco]
-
A.
Jaleco
Jaleco was a Japanese video game company known for developing and publishing arcade and home console titles from the 1980s through the early 2000s.
-
B.
Namco Bandai Games
chosen
Namco Bandai Games is a major Japanese video game publisher and developer known for franchises such as Tekken, Pac-Man, and the Tales series.
-
C.
Sega
Sega is a Japanese video game and entertainment company best known for its iconic consoles and franchises such as Sonic the Hedgehog.
-
D.
Konami
Konami is a major Japanese entertainment company best known for developing and publishing popular video game franchises such as Metal Gear, Castlevania, and Silent Hill.
-
E.
Toie
Toie is a given name, often used as a short or informal form of the name Toie Roberts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad143c48190b9d52c331e8101d6 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:36 p.m.