Triple
T8016805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aden Road corridor |
E186637
|
entity |
| Predicate | traversesLandscapeType |
P71042
|
FINISHED |
| Object | rural landscape |
—
|
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: rural landscape | Statement: [Aden Road corridor, traversesLandscapeType, rural landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traversesLandscapeType Context triple: [Aden Road corridor, traversesLandscapeType, rural landscape]
-
A.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
flowsThroughLandscape
chosen
Indicates that something (typically a fluid or moving entity) passes through or traverses a particular landscape or terrain.
-
C.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
D.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
E.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df37a00819088780e5461bc5b41 |
completed | March 31, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.