Triple
T13227915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | smart EQ fortwo |
E314928
|
entity |
| Predicate | turningCircle |
P108621
|
FINISHED |
| Object | very small turning radius for city driving |
—
|
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: very small turning radius for city driving | Statement: [smart EQ fortwo, turningCircle, very small turning radius for city driving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turningCircle Context triple: [smart EQ fortwo, turningCircle, very small turning radius for city driving]
-
A.
hasCircle
Indicates that one entity possesses, contains, or includes a circle as part of its structure or composition.
-
B.
circleType
Indicates the specific classification or category of a circle within a given context or system.
-
C.
turns
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
D.
roundel
Indicates that one entity bears, displays, or is marked with a circular emblem or symbol representing another entity.
-
E.
circles
Indicates that one entity moves around another entity along a roughly circular path or orbit.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:21 p.m.