Triple
T12119941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerta de Europa towers |
E288665
|
entity |
| Predicate | leanAngle |
P103387
|
FINISHED |
| Object | 15 degrees |
—
|
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: 15 degrees | Statement: [Puerta de Europa towers, leanAngle, 15 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leanAngle Context triple: [Puerta de Europa towers, leanAngle, 15 degrees]
-
A.
dropAngle
Indicates the angle at which something is dropped or released relative to a reference direction or surface.
-
B.
legOrientation
Indicates the relative positioning or directional alignment of an entity’s leg(s) with respect to a reference frame or another object.
-
C.
angleProperty
Indicates that a relationship specifies a particular geometric or quantitative characteristic (such as measure, type, or orientation) of an angle between entities.
-
D.
bendAngle
Indicates the degree to which one part is bent relative to another, typically measured as the angle formed at their joint or intersection.
-
E.
lowerInclinationAngle
Indicates that one entity has a smaller or more downward-tilted inclination angle compared to another entity.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916481a008190ae66677b9e6dd961 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:49 p.m.