Triple
T3981882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CREA corpus |
E85775
|
entity |
| Predicate | registerCoverage |
P53173
|
FINISHED |
| Object | written Spanish |
—
|
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: written Spanish | Statement: [CREA corpus, registerCoverage, written Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registerCoverage Context triple: [CREA corpus, registerCoverage, written Spanish]
-
A.
formatCoverage
Indicates how thoroughly or extensively a particular format or formatting scheme is applied or supported in a given context.
-
B.
coverageScope
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
C.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
D.
keyCoverage
Indicates that one entity provides coverage, protection, or applicability for another in a way that is essential or central to its function or requirements.
-
E.
isCoveredBy
Indicates that one entity is physically or conceptually overlaid, protected, or enclosed by another entity.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa3cf4048190837f9ec5fa8e95e3 |
completed | March 9, 2026, 4:50 p.m. |
Created at: March 9, 2026, 3:33 p.m.