Triple
T19771990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cascade-Correlation learning architecture |
E474908
|
entity |
| Predicate | usesWeightFreezing |
P137268
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cascade-Correlation learning architecture, usesWeightFreezing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWeightFreezing Context triple: [Cascade-Correlation learning architecture, usesWeightFreezing, true]
-
A.
neverFreezes
Indicates that the subject is never in a state of freezing, i.e., it does not reach or experience freezing conditions under any circumstances.
-
B.
freezesOver
Indicates that a liquid surface becomes solid due to low temperatures, typically forming a layer of ice over it.
-
C.
reasonForNotFreezing
Indicates the explanation or cause for why a particular thing, process, or condition is not frozen or has not been subjected to freezing.
-
D.
isIceFree
Indicates that a location, surface, or object is not covered by ice or free from ice presence.
-
E.
hasTypicalFreezingPoint
Indicates the temperature at which a substance normally changes from liquid to solid under standard conditions.
- F. None of above. chosen
Provenance (4 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535ce4d08190a1dfca2df95a8631 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:48 p.m.