Triple
T24440181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | learning curve |
E616236
|
entity |
| Predicate | canHaveShape |
P131712
|
FINISHED |
| Object | steep initial improvement followed by plateau |
—
|
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: steep initial improvement followed by plateau | Statement: [learning curve, canHaveShape, steep initial improvement followed by plateau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canHaveShape Context triple: [learning curve, canHaveShape, steep initial improvement followed by plateau]
-
A.
hasArchShape
Indicates that something possesses or exhibits an arched or curved shape.
-
B.
hasShapeModel
Indicates that an entity is associated with a specific geometric or structural shape model that represents its form.
-
C.
hasHemShape
Indicates that an item possesses a specific form or contour of its hem or lower edge.
-
D.
hasApparentShape
chosen
Indicates that one entity is perceived or observed to have a particular shape or form, regardless of its true or physical structure.
-
E.
hasDistinctiveShape
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2978a5cac81909d2141b606714fd4 |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.