Triple
T20794705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Area Risk Protection Insurance |
E511880
|
entity |
| Predicate | dataSourceForCoverage |
P46377
|
FINISHED |
| Object | county yield data |
—
|
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: county yield data | Statement: [Area Risk Protection Insurance, dataSourceForCoverage, county yield data]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataSourceForCoverage Context triple: [Area Risk Protection Insurance, dataSourceForCoverage, county yield data]
-
A.
dataSourceFor
chosen
Indicates that one entity serves as the origin or provider of data that is used or consumed by another entity.
-
B.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
-
C.
dataSourceForApportionment
Indicates that one entity serves as the source of data used to determine or calculate the apportionment of another entity.
-
D.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
E.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2abbcc8819091bb0225a0650ab6 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0575b1c81908d010223fcd1213e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:39 p.m.