Triple
T21061060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SKActionTimingMode |
E518846
|
entity |
| Predicate | easeInEaseOutDescription |
P57135
|
FINISHED |
| Object | starts slowly, speeds up, then slows down at the end |
—
|
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: starts slowly, speeds up, then slows down at the end | Statement: [SKActionTimingMode, easeInEaseOutDescription, starts slowly, speeds up, then slows down at the end]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: easeInEaseOutDescription Context triple: [SKActionTimingMode, easeInEaseOutDescription, starts slowly, speeds up, then slows down at the end]
-
A.
movesSlightlyOverTime
Indicates that an entity changes its position or state gradually or by a small amount over a period of time.
-
B.
hasSlowMovement
Indicates that an entity exhibits movement that is slower than a normal or expected speed.
-
C.
accelerates
Indicates that one entity causes an increase in the speed or rate of change of another entity or process.
-
D.
transitionCharacteristic
chosen
Indicates a relationship where an entity is characterized by how it changes state or condition over time or between phases.
-
E.
bounceCharacteristics
Indicates the specific way in which something bounces, such as its rebound height, frequency, or pattern of motion after impact.
- 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feaf3edc81909423e039cac6bd87 |
completed | April 21, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:38 p.m.