Triple
T17520582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | StandardScaler |
E426669
|
entity |
| Predicate | parameterReusedOn |
P91997
|
FINISHED |
| Object | test data |
—
|
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: test data | Statement: [StandardScaler, parameterReusedOn, test data]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parameterReusedOn Context triple: [StandardScaler, parameterReusedOn, test data]
-
A.
reusedIn
chosen
Indicates that something previously used in one context or instance is used again in another context or instance.
-
B.
nameReusedFor
Indicates that an existing name has been used again for a different entity or instance, rather than introducing a completely new name.
-
C.
partiallyReusedAs
Indicates that one entity is used again as part of another entity, but only to a limited or incomplete extent rather than in its entirety.
-
D.
notReusedFor
Indicates that something is not used again for a subsequent purpose, context, or instance.
-
E.
keyReuse
Indicates that the same key is used multiple times, rather than being uniquely generated or dedicated for a single use or context.
- 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.