Triple
T1427947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss map |
E30376
|
entity |
| Predicate | inverseImage |
P28978
|
FINISHED |
| Object | set of points on surface with same normal direction |
—
|
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: set of points on surface with same normal direction | Statement: [Gauss map, inverseImage, set of points on surface with same normal direction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inverseImage Context triple: [Gauss map, inverseImage, set of points on surface with same normal direction]
-
A.
inverseFlattening
Indicates the reciprocal of the flattening ratio of an ellipsoid, expressing how much it deviates from a perfect sphere.
-
B.
isInverseOf
Indicates that one relation reverses the direction of another, so that if the original relates A to B, its inverse relates B to A.
-
C.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
D.
publicImage
Indicates how an entity is perceived or represented by the general public or broader audience.
-
E.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.