Triple
T15465384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabbit |
E372018
|
entity |
| Predicate | franchise |
P1500
|
FINISHED |
| Object | Mario series |
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: Mario series | Statement: [Nabbit, franchise, Mario series]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario series Context triple: [Nabbit, franchise, Mario series]
-
A.
Super Mario series
chosen
The Super Mario series is Nintendo’s flagship platform game franchise starring Mario in a wide variety of adventures across imaginative worlds.
-
B.
Mario vs. Donkey Kong series
The Mario vs. Donkey Kong series is a puzzle-platform video game franchise in which Mario navigates intricate, toy-themed levels to outwit Donkey Kong and solve object-based challenges.
-
C.
Yoshi series
The Yoshi series is a platform game franchise by Nintendo that stars the dinosaur Yoshi in colorful, often puzzle-oriented adventures spun off from the Super Mario series.
-
D.
Mario
Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
-
E.
Mario
Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f680cec8190836a5ec841dee224 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa121f814819096a69cf5ef0003ee |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 3:33 a.m.