Triple
T10245878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austin Powers |
E240210
|
entity |
| Predicate | enemy |
P4567
|
FINISHED |
| Object | Dr. Evil |
E240211
|
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: Dr. Evil | Statement: [Austin Powers, enemy, Dr. Evil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dr. Evil Context triple: [Austin Powers, enemy, Dr. Evil]
-
A.
Dr. Evil
chosen
Dr. Evil is the bald, over-the-top supervillain and comedic arch-nemesis of Austin Powers in the Austin Powers film series.
-
B.
Dr. Heinz Doofenshmirtz
Dr. Heinz Doofenshmirtz is a bumbling, melodramatic evil scientist and recurring antagonist from the animated series "Phineas and Ferb," known for his elaborate "inator" inventions and comedic schemes.
-
C.
Doctor Neo Cortex
Doctor Neo Cortex is the mad scientist and primary villain of the Crash Bandicoot video game series, known for his schemes to conquer the world using genetically enhanced animals.
-
D.
Dr. Nefario
Dr. Nefario is the elderly, gadget-inventing mad scientist who serves as Gru’s loyal but eccentric assistant in the Despicable Me franchise.
-
E.
Dr. Igor
Dr. Igor is a psychiatrist in Paulo Coelho’s novel "Veronika Decides to Die," known for his controversial experimental approach to treating patients in a mental institution.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22cfe1c8190afae178e11a59b8b |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d74fea9c508190b92f7205424861cd |
completed | April 9, 2026, 7:06 a.m. |
Created at: April 6, 2026, 11:26 a.m.