Triple
T15922455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mur de Huy |
E386124
|
entity |
| Predicate | approximateMaximumGradient |
P46516
|
FINISHED |
| Object | about 19 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 19 percent | Statement: [Mur de Huy, approximateMaximumGradient, about 19 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateMaximumGradient Context triple: [Mur de Huy, approximateMaximumGradient, about 19 percent]
-
A.
maximumGradient
chosen
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
B.
averageGradient
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
C.
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.
-
D.
hasMaximumGradeBeforeCurves
Indicates that an entity’s highest achievable grade is specified prior to any grading curves or adjustments being applied.
-
E.
acceleratingGradient
Indicates that a process, change, or effect is increasing in rate over time, becoming progressively faster or more intense.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.