Triple
T11739869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambert azimuthal equal-area projection |
E279123
|
entity |
| Predicate | typicalMapShape |
P101094
|
FINISHED |
| Object | circle |
—
|
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: circle | Statement: [Lambert azimuthal equal-area projection, typicalMapShape, circle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMapShape Context triple: [Lambert azimuthal equal-area projection, typicalMapShape, circle]
-
A.
typicalMapping
Indicates a standard or commonly used correspondence between elements of one set, structure, or representation and those of another.
-
B.
mapsDepict
Indicates that maps visually represent or illustrate the geographic features, locations, or spatial relationships of something.
-
C.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
D.
topographicMap
Indicates a mapping relationship where a representation shows the physical terrain features and elevation contours of a geographic area.
-
E.
geographicalRepresentation
Indicates that one entity serves as a geographic depiction, model, or mapping of another entity’s location, area, or spatial characteristics.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f025f88190a39280806c9d7c33 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:41 p.m.