Triple
T12597427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heun’s method |
E300767
|
entity |
| Predicate | correctorSlopeComputation |
P105617
|
FINISHED |
| Object | average of initial and predicted slopes |
—
|
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: average of initial and predicted slopes | Statement: [Heun’s method, correctorSlopeComputation, average of initial and predicted slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correctorSlopeComputation Context triple: [Heun’s method, correctorSlopeComputation, average of initial and predicted slopes]
-
A.
isOnSlopeOf
Indicates that one entity is located on the inclined surface or side of another entity, typically a sloping terrain or structure.
-
B.
hasSlopeFeature
Indicates that an entity possesses or is characterized by a particular slope-related property or feature.
-
C.
slopeType
Indicates the classification of a slope based on its geometric or physical characteristics, such as steepness, shape, or orientation.
-
D.
slopeUse
Indicates how a particular slope or gradient is utilized or purposed in relation to another entity.
-
E.
slopeAspect
Indicates the compass direction that a slope or surface is facing.
- F. None of above. chosen
Provenance (4 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954e351f88190869220d46e0ce282 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 9, 2026, 5:08 p.m.