Triple
T3716412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Waldseemüller |
E81540
|
entity |
| Predicate | mapProjectionUsed |
P1986
|
FINISHED |
| Object | cordiform projection |
—
|
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: cordiform projection | Statement: [Martin Waldseemüller, mapProjectionUsed, cordiform projection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapProjectionUsed Context triple: [Martin Waldseemüller, mapProjectionUsed, cordiform projection]
-
A.
mapProjection
chosen
Indicates the specific method or transformation used to represent locations from the curved surface of the Earth onto a flat map.
-
B.
cartographicContext
Indicates the mapping or geographic framework within which something is spatially represented or interpreted.
-
C.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
D.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
E.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc9cf77dc819098979094172d82d1 |
completed | March 8, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.