Triple
T28559249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filstalbahn |
E723088
|
entity |
| Predicate | hasNotableGradient |
P642
|
FINISHED |
| Object | Geislinger Steige |
—
|
NE NERFINISHED |
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: Geislinger Steige | Statement: [Filstalbahn, hasNotableGradient, Geislinger Steige]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableGradient Context triple: [Filstalbahn, hasNotableGradient, Geislinger Steige]
-
A.
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.
-
B.
hasGradientSection
Indicates that an entity includes a portion or segment where some property changes gradually rather than remaining constant.
-
C.
usesGradientInformation
Indicates that an entity performs its operation by leveraging gradient (derivative) information, typically to guide optimization or learning steps.
-
D.
hasNotableFeature
chosen
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
E.
hasApproachGradient
Indicates that one entity is associated with the rate of change in elevation or slope along the approach to another entity.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: April 28, 2026, 3:47 a.m.