Triple
T6993218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zig Zag Road |
E162134
|
entity |
| Predicate | hasMaximumGradient |
P46516
|
FINISHED |
| Object | about 10 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 10 percent | Statement: [Zig Zag Road, hasMaximumGradient, about 10 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumGradient Context triple: [Zig Zag Road, hasMaximumGradient, about 10 percent]
-
A.
maximumGradient
chosen
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
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.
hasMaximumGradeBeforeCurves
Indicates that an entity’s highest achievable grade is specified prior to any grading curves or adjustments being applied.
-
D.
hasMaximumValue
Indicates that one value in a set is the greatest or highest possible according to a specified criterion.
-
E.
hasMaximumGrade
Indicates that an entity possesses the highest possible grade or score within a defined grading or evaluation system.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc30fdc81909244d83c8178755c |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:32 p.m.