Triple
T29871147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nintendo Revolution |
E758596
|
entity |
| Predicate | notableFranchisesFeatured |
P8079
|
FINISHED |
| Object | Super Mario |
E406903
|
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: Super Mario | Statement: [Nintendo Revolution, notableFranchisesFeatured, Super Mario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFranchisesFeatured Context triple: [Nintendo Revolution, notableFranchisesFeatured, Super Mario]
-
A.
notableSeriesFranchise
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
B.
notableFranchiseAdapted
Indicates that a work has been adapted from a notable franchise into another medium or format.
-
C.
gameFranchise
Indicates that one entity is a video game franchise to which the other entity (such as a specific game, character, or related media) belongs or is associated.
-
D.
includesFranchisesFrom
Indicates that one entity contains or encompasses franchises that originate from another entity.
-
E.
hasNotableFranchise
chosen
Indicates that an entity is associated with a well-known, significant, or widely recognized franchise.
- F. None of above.
Provenance (4 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26f1cf642881909362077f3082b1dd |
completed | June 8, 2026, 4:46 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 5:53 p.m.