Triple
T11003503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Show and Tell: A Neural Image Caption Generator |
E260056
|
entity |
| Predicate | decoder |
P63105
|
FINISHED |
| Object | recurrent 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: recurrent neural network | Statement: [Show and Tell: A Neural Image Caption Generator, decoder, recurrent neural network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decoder Context triple: [Show and Tell: A Neural Image Caption Generator, decoder, recurrent neural network]
-
A.
deciphers
Indicates the action of successfully interpreting or figuring out the meaning of something that is difficult to understand or encoded.
-
B.
coDecipherer
Indicates that two or more entities jointly participated in deciphering or decoding something together.
-
C.
decodingMethod
Indicates the technique or process used to convert encoded or encrypted data back into its original, interpretable form.
-
D.
decipheredFrom
Indicates that something has been interpreted, decoded, or understood based on information derived from another source.
-
E.
interpreter
chosen
Indicates that one entity serves to translate or render the meaning of another entity (such as language, code, or symbols) into an understandable or executable form.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797546f448190946ee6442d657dc5 |
completed | April 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.