Triple
T1460153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario |
E31492
|
entity |
| Predicate | ally |
P4662
|
FINISHED |
| Object | Toad |
E75271
|
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: Toad | Statement: [Mario, ally, Toad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toad Context triple: [Mario, ally, Toad]
-
A.
Toad
chosen
Toad is a loyal, mushroom-capped resident of the Mushroom Kingdom in the Super Mario franchise, known for assisting Mario and his friends on their adventures.
-
B.
Frog
Frog is the internal codename used by Apple for the Macintosh SE personal computer during its development.
-
C.
Blooper
Blooper is the fuzzy, energetic costumed mascot of Major League Baseball’s Atlanta Braves, known for entertaining fans with comedic antics at games.
-
D.
Gobbo
Gobbo is a mischievous goblin character who serves as one of the main troublemaking antagonists in Enid Blyton’s Noddy stories.
-
E.
Grenouilles
Grenouilles is one of the prestigious Grand Cru vineyard sites in the Chablis wine region of Burgundy, France, known for producing high-quality Chardonnay wines.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59d6dd88190b8ff3bda90aef7e2 |
completed | March 1, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e786a208190a57c4e1878c66517 |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 8 p.m.