Triple
T15313719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Visual Geometry Group |
E366100
|
entity |
| Predicate | hasMember |
P10
|
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: [Visual Geometry Group, hasMember, Andrew Zisserman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Zisserman Context triple: [Visual Geometry Group, hasMember, 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.
Abraham Girshick
Abraham Girshick was an American statistician known for his contributions to statistical decision theory and his work during World War II with Columbia University's Statistical Research Group.
-
C.
Alexei Efros
Alexei Efros is a prominent computer scientist known for his influential work in computer vision and computational photography.
-
D.
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.
-
E.
Jia Deng
Jia Deng is a computer scientist known for his influential work in computer vision and machine learning, particularly as a co-creator of the large-scale image dataset ImageNet.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd050108190a584543cb93943a4 |
completed | April 16, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8a3da3881909b50cfbec0543adc |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.