Triple
T1579601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forest of Bowland |
E33730
|
entity |
| Predicate | protectedAreaIUCNCategory |
P32835
|
FINISHED |
| Object | V |
—
|
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: V | Statement: [Forest of Bowland, protectedAreaIUCNCategory, V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectedAreaIUCNCategory Context triple: [Forest of Bowland, protectedAreaIUCNCategory, V]
-
A.
partOfProtectedAreaCategory
Indicates that one protected area belongs to, or is classified under, a specific protected area category.
-
B.
typeOfProtectedAreasManaged
Indicates the specific categories or kinds of protected areas that an entity is responsible for managing.
-
C.
hasProtectedAreaStatus
Indicates that an area is officially designated and managed as a protected area under relevant conservation or legal frameworks.
-
D.
percentageProtectedArea
Indicates the proportion of a given area that is designated and managed as protected land or water.
-
E.
protectedAreaCountry
Indicates that a protected area is located within and legally falls under the jurisdiction of a specific country.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abacfb1144819080c5687175aba1e1 |
completed | March 7, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69aa61b0f5bc8190b1dc272990a59c13 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69abacf991148190b20521c063f93bfd |
completed | March 7, 2026, 4:43 a.m. |
Created at: March 4, 2026, 7:27 p.m.