Triple
T2114123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noise protocol framework |
E42567
|
entity |
| Predicate | hasAuthor |
P4244
|
FINISHED |
| Object | Trevor Perrin |
E235259
|
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: Trevor Perrin | Statement: [Noise protocol framework, hasAuthor, Trevor Perrin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trevor Perrin Context triple: [Noise protocol framework, hasAuthor, Trevor Perrin]
-
A.
Trevor Perrin
chosen
Trevor Perrin is a cryptographer and software engineer best known for creating the Noise protocol framework and co-designing the Signal Protocol used in secure messaging.
-
B.
Brandon Perlman
Brandon Perlman is the son of American actor Ron Perlman and works as a music producer and DJ.
-
C.
Jonathan Teplitzky
Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
-
D.
Steve Goodrich
Steve Goodrich is a former American basketball player best known as a standout center for Princeton University in the late 1990s, where he helped lead the Tigers to national prominence.
-
E.
Christopher Lennertz
Christopher Lennertz is an American composer best known for his film, television, and video game scores, including work on major comedies, action films, and popular series like Supernatural.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb05b51c81908a78c816f492c45c |
completed | March 7, 2026, 5:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5194abec8190aab8b7a9ef98da92 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:43 p.m.