Triple
T20192646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super FX |
E493011
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Mario Chip
Mario Chip is an alternate name for the Super FX, a coprocessor chip used in certain Super Nintendo games to enable advanced 3D graphics and visual effects.
|
E1416216
|
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: Mario Chip | Statement: [Super FX, alsoKnownAs, Mario Chip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario Chip Context triple: [Super FX, alsoKnownAs, Mario Chip]
-
A.
Mário
Mário is a masculine given name of Latin origin, widely used in Portuguese- and Italian-speaking countries.
-
B.
Wario
Wario is a greedy, mischievous antihero in Nintendo’s Mario franchise, known for his brutish strength, distinctive yellow and purple outfit, and starring role in the Wario Land and WarioWare game series.
-
C.
Yoshi
Yoshi is a friendly, dinosaur-like character from Nintendo’s Mario franchise, known for his long tongue, egg-throwing abilities, and frequent role as Mario’s companion and steed.
-
D.
Mario Banana
Mario Banana is a film featuring the underground drag performer and Warhol superstar Mario Montez.
-
E.
Mario
Mario is the young, aspiring writer and romantic protagonist of Mario Vargas Llosa’s novel "Aunt Julia and the Scriptwriter."
- 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: Mario Chip Triple: [Super FX, alsoKnownAs, Mario Chip]
Generated description
Mario Chip is an alternate name for the Super FX, a coprocessor chip used in certain Super Nintendo games to enable advanced 3D graphics and visual effects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mario Chip Target entity description: Mario Chip is an alternate name for the Super FX, a coprocessor chip used in certain Super Nintendo games to enable advanced 3D graphics and visual effects.
-
A.
Mário
Mário is a masculine given name of Latin origin, widely used in Portuguese- and Italian-speaking countries.
-
B.
Wario
Wario is a greedy, mischievous antihero in Nintendo’s Mario franchise, known for his brutish strength, distinctive yellow and purple outfit, and starring role in the Wario Land and WarioWare game series.
-
C.
Yoshi
Yoshi is a friendly, dinosaur-like character from Nintendo’s Mario franchise, known for his long tongue, egg-throwing abilities, and frequent role as Mario’s companion and steed.
-
D.
Mario Banana
Mario Banana is a film featuring the underground drag performer and Warhol superstar Mario Montez.
-
E.
Mario
Mario is the young, aspiring writer and romantic protagonist of Mario Vargas Llosa’s novel "Aunt Julia and the Scriptwriter."
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad654648190a27521e6e8ea40c5 |
completed | April 20, 2026, 6:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a083c885e788190888c76b925f290e0 |
completed | May 16, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_6a083d20eb908190b82d668beed3789b |
completed | May 16, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a083e49d5988190b41e8ce5bcebeca5 |
completed | May 16, 2026, 9:52 a.m. |
Created at: April 11, 2026, 11:37 p.m.