Triple
T12370113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Progressive GAN |
E294977
|
entity |
| Predicate | evaluationMetric |
P21575
|
FINISHED |
| Object | Inception Score |
E290873
|
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: Inception Score | Statement: [Progressive GAN, evaluationMetric, Inception Score]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inception Score Context triple: [Progressive GAN, evaluationMetric, Inception Score]
-
A.
Inception Score
chosen
Inception Score is a quantitative metric used to assess the quality and diversity of images generated by generative models by analyzing their classifiability and distribution across categories using a pretrained Inception network.
-
B.
Fréchet Inception Distance
Fréchet Inception Distance is a widely used quantitative metric that measures the similarity between real and generated images by comparing their feature distributions extracted from a pretrained Inception network.
-
C.
Kullback–Leibler divergence
Kullback–Leibler divergence is a fundamental information-theoretic measure that quantifies how one probability distribution differs from a reference distribution.
-
D.
INTERPOL Diffusion
INTERPOL Diffusion is a decentralized alert mechanism used within the INTERPOL network to rapidly share information about wanted persons, threats, or criminal activity among selected member countries.
-
E.
CIDEr
CIDEr is an automatic evaluation metric designed to assess the quality of image captions by measuring their consensus with human-written descriptions.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa65a608190a1597a49751185a8 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62abfd9c081909803691d3fc4f149 |
completed | May 2, 2026, 4:48 p.m. |
Created at: April 8, 2026, 9:54 p.m.