Triple
T18016180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CelebA |
E431002
|
entity |
| Predicate | relatedDataset |
P91587
|
FINISHED |
| Object | CelebA-HQ |
—
|
NE NERFINISHED |
How this triple was built (4 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: CelebA-HQ | Statement: [CelebA, relatedDataset, CelebA-HQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CelebA-HQ Context triple: [CelebA, relatedDataset, CelebA-HQ]
-
A.
CelebA
CelebA is a large-scale face attributes dataset widely used in computer vision research for tasks like facial recognition, attribute prediction, and generative modeling.
-
B.
FFHQ
FFHQ (Flickr-Faces-HQ) is a high-quality, large-scale dataset of diverse human face images widely used for training and evaluating generative image models.
-
C.
LFW
LFW is the IATA airport code for Lomé–Tokoin International Airport, the main airport serving Lomé, the capital of Togo.
-
D.
StyleGAN
StyleGAN is a state-of-the-art generative adversarial network architecture known for producing highly realistic, controllable images by manipulating disentangled style representations at different layers of the network.
-
E.
Pix2Pix
Pix2Pix is a conditional generative adversarial network (cGAN) framework for paired image-to-image translation tasks, such as turning sketches into photos or maps into satellite images.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CelebA-HQ Target entity description: CelebA-HQ is a high-resolution, higher-quality version of the CelebA face dataset widely used for training and evaluating generative models and other computer vision algorithms on human facial images.
-
A.
CelebA
chosen
CelebA is a large-scale face attributes dataset widely used in computer vision research for tasks like facial recognition, attribute prediction, and generative modeling.
-
B.
FFHQ
FFHQ (Flickr-Faces-HQ) is a high-quality, large-scale dataset of diverse human face images widely used for training and evaluating generative image models.
-
C.
LFW
LFW is the IATA airport code for Lomé–Tokoin International Airport, the main airport serving Lomé, the capital of Togo.
-
D.
StyleGAN
StyleGAN is a state-of-the-art generative adversarial network architecture known for producing highly realistic, controllable images by manipulating disentangled style representations at different layers of the network.
-
E.
Pix2Pix
Pix2Pix is a conditional generative adversarial network (cGAN) framework for paired image-to-image translation tasks, such as turning sketches into photos or maps into satellite images.
- F. None of above.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedDataset Context triple: [CelebA, relatedDataset, CelebA-HQ]
-
A.
linkedDataset
chosen
Indicates that one dataset is connected or associated with another dataset, typically to show a relevant relationship or dependency between them.
-
B.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
C.
relatedCohort
Indicates that two or more entities are associated through membership in, or connection to, the same cohort or grouped population.
-
D.
relatedMetric
Indicates that one metric has a defined relationship or dependency with another metric.
-
E.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
- F. None of above.
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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.