Triple
T6993217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zig Zag Road |
E162134
|
entity |
| Predicate | hasApproximateAverageGradient |
P54393
|
FINISHED |
| Object | about 4 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 4 percent | Statement: [Zig Zag Road, hasApproximateAverageGradient, about 4 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateAverageGradient Context triple: [Zig Zag Road, hasApproximateAverageGradient, about 4 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.
acceleratingGradient
Indicates that a process, change, or effect is increasing in rate over time, becoming progressively faster or more intense.
-
D.
usesGradientInformation
Indicates that an entity performs its operation by leveraging gradient (derivative) information, typically to guide optimization or learning steps.
-
E.
hasApproximateValue
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
- 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.