Triple
T952449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanmore Common |
E20551
|
entity |
| Predicate | hasLandscapeCharacter |
P7342
|
FINISHED |
| Object | semi-natural 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: semi-natural woodland | Statement: [Stanmore Common, hasLandscapeCharacter, semi-natural woodland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeCharacter Context triple: [Stanmore Common, hasLandscapeCharacter, semi-natural woodland]
-
A.
hasLandscapeType
chosen
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasOrientation
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
-
C.
hasLigatures
Indicates that one writing system, font, or text includes combined character forms (ligatures) that join two or more individual glyphs into a single symbol.
-
D.
hasWritingDirection
Indicates the direction in which writing or text is read or written for a given script, language, or text system.
-
E.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3d757d08190a475cf47febd05ae |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a045308190ab94f3adab40db8d |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.