Triple
T29168171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZZ method |
E739378
|
entity |
| Predicate | turningStyle |
P166380
|
FINISHED |
| Object | rotationless or low-rotation F2L |
—
|
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: rotationless or low-rotation F2L | Statement: [ZZ method, turningStyle, rotationless or low-rotation F2L]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turningStyle Context triple: [ZZ method, turningStyle, rotationless or low-rotation F2L]
-
A.
turningCircle
Indicates the radius or size of the circular path an object follows when it turns, typically reflecting how tightly it can change direction.
-
B.
steeringType
Indicates the kind or mechanism of steering control used to direct the movement of an entity.
-
C.
trailOrientation
Indicates the directional alignment or facing direction of a trail relative to a reference frame or compass directions.
-
D.
roadDirectionConvention
Indicates the customary rule in a place for which side of the road vehicles are expected to drive on.
-
E.
crossingStyle
Indicates the manner or method by which one entity crosses or traverses another (such as a boundary, path, or medium).
- 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_69f07cb6394c8190ab7842c48e699e2a |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f662d73ac8819084ad24fb84e85f35 |
completed | May 2, 2026, 8:47 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65fb2ead08190b06677d4d6ea1ea8 |
completed | May 2, 2026, 8:33 p.m. |
Created at: April 28, 2026, 11:51 a.m.