Triple
T3448419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Mitzevich |
E72731
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Nick Mitzevich |
E72731
|
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: Nick Mitzevich | Statement: [Nick Mitzevich, knownAs, Nick Mitzevich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Mitzevich Context triple: [Nick Mitzevich, knownAs, Nick Mitzevich]
-
A.
Nick Mitzevich
chosen
Nick Mitzevich is an Australian art curator and museum director known for leading major national art institutions, including the National Gallery of Australia.
-
B.
Jim Messina
Jim Messina is an American political strategist best known for managing Barack Obama’s successful 2012 presidential re-election campaign.
-
C.
Matthew Freund
Matthew Freund is a film editor known for his work on the comedy movie "Fist Fight."
-
D.
Jon Oberheide
Jon Oberheide is a cybersecurity entrepreneur and researcher best known as the co-founder and former CTO of Duo Security, a leading multi-factor authentication and zero-trust security company.
-
E.
Nick Wechsler
Nick Wechsler is an American actor best known for his television roles, including playing Jack Porter on the drama series "Revenge."
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba705d988190b76d905751a337ee |
completed | March 8, 2026, 6:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360e781a88190a4df2909f32c62ab |
completed | March 13, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:16 p.m.