Triple
T8577136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karen Simonyan |
E203074
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Andrew Zisserman |
E366101
|
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: Andrew Zisserman | Statement: [Karen Simonyan, coAuthorWith, Andrew Zisserman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Zisserman Context triple: [Karen Simonyan, coAuthorWith, Andrew Zisserman]
-
A.
Andrew Zisserman
chosen
Andrew Zisserman is a prominent British computer vision researcher and professor known for foundational contributions to object recognition, image understanding, and influential deep learning architectures.
-
B.
Alexei Efros
Alexei Efros is a prominent computer scientist known for his influential work in computer vision and computational photography.
-
C.
Karen Simonyan
Karen Simonyan is a computer scientist and deep learning researcher known for influential work in neural network architectures and generative models, including contributions to systems like WaveNet.
-
D.
Cyrill Stachniss
Cyrill Stachniss is a German computer scientist and robotics researcher known for his work in mobile robotics, SLAM, and machine perception.
-
E.
Christian Szegedy
Christian Szegedy is a computer scientist and AI researcher known for his influential work on deep learning and convolutional neural networks, including contributions to the Inception architecture.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea97787481909ebbaa45f59cbdaa |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce899dd7d48190b44338b92ad68bd0 |
completed | April 2, 2026, 3:22 p.m. |
Created at: March 30, 2026, 6:22 p.m.