Triple
T7581753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss–Matuyama geomagnetic reversal |
E179503
|
entity |
| Predicate | hasGlobalExtent |
P32890
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [Gauss–Matuyama geomagnetic reversal, hasGlobalExtent, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlobalExtent Context triple: [Gauss–Matuyama geomagnetic reversal, hasGlobalExtent, global]
-
A.
hasGlobalRegion
Indicates that an entity is associated with or belongs to a specific global geographic region.
-
B.
hasApproximateExtent
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
C.
hasGlobalDistribution
chosen
Indicates that the related entity occurs, operates, or is present across most or all regions of the world rather than being confined to a specific locality or region.
-
D.
hasGlobalPlan
Indicates that an entity possesses or is associated with an overarching, comprehensive plan that applies at a global or system-wide level.
-
E.
maximumExtent
Indicates the greatest or furthest degree, size, or range to which something can extend or apply within a given context.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f978341081909e009c410ffc5039 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:52 p.m.