Triple
T36489806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LRCN |
E899022
|
entity |
| Predicate | featureExtractionBy |
P56708
|
FINISHED |
| Object | convolutional neural network |
—
|
LITERAL 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: convolutional neural network | Statement: [LRCN, featureExtractionBy, convolutional neural network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureExtractionBy Context triple: [LRCN, featureExtractionBy, convolutional neural network]
-
A.
sharesFeatureExtractor
chosen
Indicates that two or more models or components use the same feature extraction mechanism or module.
-
B.
featuresMethod
Indicates that an entity includes or provides a particular method as part of its functionality or behavior.
-
C.
featuresRepresentationOf
Indicates that one entity visually or symbolically depicts, portrays, or includes a representation of another entity.
-
D.
featuresTransformationOf
Indicates that something includes or presents a transformation or change applied to another entity.
-
E.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.