Triple
T14482576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alto de Jaizkibel |
E359146
|
entity |
| Predicate | hasAverageGradient |
P54393
|
FINISHED |
| Object | about 5.8 percent |
—
|
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: about 5.8 percent | Statement: [Alto de Jaizkibel, hasAverageGradient, about 5.8 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageGradient Context triple: [Alto de Jaizkibel, hasAverageGradient, about 5.8 percent]
-
A.
averageGradient
chosen
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
B.
hasGradient
Indicates that one entity possesses or is characterized by a gradual change in value, intensity, or property across its extent or between two points.
-
C.
usesGradientInformation
Indicates that an entity performs its operation by leveraging gradient (derivative) information, typically to guide optimization or learning steps.
-
D.
hasGradientSection
Indicates that an entity includes a portion or segment where some property changes gradually rather than remaining constant.
-
E.
averageGradientFromOvaro
Indicates the average slope or steepness calculated starting from the location Ovaro along a specified route or segment.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924bc548819087a2f693840d7426 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.