Triple
T13331357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Drake |
E317579
|
entity |
| Predicate | voicedBy |
P2181
|
FINISHED |
| Object | Nolan North |
E863678
|
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: Nolan North | Statement: [Nathan Drake, voicedBy, Nolan North]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nolan North Context triple: [Nathan Drake, voicedBy, Nolan North]
-
A.
Nolan North
chosen
Nolan North is a prolific American voice actor best known for his performances in major video game franchises such as Uncharted, Assassin’s Creed, and Destiny.
-
B.
Crispin Freeman
Crispin Freeman is an American voice actor known for his work in anime, video games, and animation, including prominent roles in series like Hellsing, Naruto, and Overwatch.
-
C.
Tom Kane
Tom Kane is an American voice actor best known for his extensive work in animation and video games, including roles in the Star Wars franchise.
-
D.
Eric Bauza
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
-
E.
Kyle Howard
Kyle Howard is an American actor best known for his comedic roles in television series and films, including prominent parts in sitcoms.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992fffa0819086610ae3bed2e2f9 |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f329e148190a7741344b27ea663 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:30 p.m.