Triple
T18016053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COCO |
E431000
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | COCO captioning challenge |
—
|
NE NERFINISHED |
How this triple was built (3 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: COCO captioning challenge | Statement: [COCO, associatedWith, COCO captioning challenge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: COCO captioning challenge Context triple: [COCO, associatedWith, COCO captioning challenge]
-
A.
CLIP
CLIP is an OpenAI model that learns joint representations of images and text, enabling tasks like zero-shot image classification and natural language-based image retrieval.
-
B.
Flickr30k
Flickr30k is a large-scale image dataset of 31,000 photographs each paired with multiple human-written captions, widely used for training and evaluating image captioning and vision-language models.
-
C.
Show and Tell: A Neural Image Caption Generator
"Show and Tell: A Neural Image Caption Generator" is a pioneering deep learning model that automatically generates natural-language descriptions for images by combining convolutional and recurrent neural networks.
-
D.
Images and Words
Images and Words is a landmark 1992 progressive metal album by Dream Theater, widely credited with bringing the band mainstream recognition and defining their signature sound.
-
E.
Flickr8k
Flickr8k is a benchmark image-captioning dataset consisting of 8,000 images each paired with multiple human-written descriptions, widely used for training and evaluating vision-language models.
- 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: COCO captioning challenge Target entity description: The COCO captioning challenge is a computer vision and natural language processing competition where systems generate descriptive text captions for images from the COCO dataset.
-
A.
CLIP
CLIP is an OpenAI model that learns joint representations of images and text, enabling tasks like zero-shot image classification and natural language-based image retrieval.
-
B.
Flickr30k
Flickr30k is a large-scale image dataset of 31,000 photographs each paired with multiple human-written captions, widely used for training and evaluating image captioning and vision-language models.
-
C.
Show and Tell: A Neural Image Caption Generator
"Show and Tell: A Neural Image Caption Generator" is a pioneering deep learning model that automatically generates natural-language descriptions for images by combining convolutional and recurrent neural networks.
-
D.
Images and Words
Images and Words is a landmark 1992 progressive metal album by Dream Theater, widely credited with bringing the band mainstream recognition and defining their signature sound.
-
E.
Flickr8k
Flickr8k is a benchmark image-captioning dataset consisting of 8,000 images each paired with multiple human-written descriptions, widely used for training and evaluating vision-language models.
- F. None of above. chosen
Provenance (2 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. |
Created at: April 10, 2026, 10:24 a.m.