Triple
T809080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackley |
E17502
|
entity |
| Predicate | hasGreenSpaceType |
P953
|
FINISHED |
| Object | woodland |
—
|
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: woodland | Statement: [Blackley, hasGreenSpaceType, woodland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenSpaceType Context triple: [Blackley, hasGreenSpaceType, woodland]
-
A.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
-
B.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
D.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
parkType
Indicates the specific category or classification of a park based on its designated use, management, or characteristics.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ac07fedc8190ab05595f25c1792f |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7221c081908068e66fe720f26d |
completed | March 1, 2026, 9:06 p.m. |
Created at: March 1, 2026, 7:38 p.m.