Triple
T17521033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TensorFlow SavedModel (via conversion) |
E426677
|
entity |
| Predicate | conversionOutput |
P79397
|
FINISHED |
| Object | model.json plus binary weight files |
—
|
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: model.json plus binary weight files | Statement: [TensorFlow SavedModel (via conversion), conversionOutput, model.json plus binary weight files]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionOutput Context triple: [TensorFlow SavedModel (via conversion), conversionOutput, model.json plus binary weight files]
-
A.
conversionTarget
chosen
Indicates that one entity serves as the intended outcome, goal, or result that another entity is meant to be converted or transformed into.
-
B.
conversionProcess
Indicates a process in which something is transformed or changed from one state, form, or representation into another.
-
C.
conversionProgram
Indicates a program or process that transforms something from one form, state, or type into another.
-
D.
convertedIn
Indicates that one entity has been transformed, changed, or translated into another form, state, or representation within a specified context.
-
E.
conversionWave
Indicates a process in which changes or transformations spread through entities or states in a sequential, wave-like manner.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d23cf08190925510344fa36f57 |
completed | April 19, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.