Triple
T4388435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coldharbour |
E99302
|
entity |
| Predicate | hasLandscapeDesignation |
P3788
|
FINISHED |
| Object | Area of Outstanding Natural Beauty |
—
|
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: Area of Outstanding Natural Beauty | Statement: [Coldharbour, hasLandscapeDesignation, Area of Outstanding Natural Beauty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeDesignation Context triple: [Coldharbour, hasLandscapeDesignation, Area of Outstanding Natural Beauty]
-
A.
hasNatureDesignation
chosen
Indicates that something has been formally assigned a specific conservation, protection, or natural-area status or designation.
-
B.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
C.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
D.
hasLandscapeDesignInfluence
Indicates that one entity has influenced or shaped the landscape design style, principles, or features of another entity.
-
E.
hasHillDesignation
Indicates that an entity is assigned a specific designation or status related to a hill.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35281900c8190882e9ccfa44ab86f |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:19 p.m.