Triple
T19925204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westgate Oxford |
E478903
|
entity |
| Predicate | hasGreenFeatures |
P83569
|
FINISHED |
| Object | roof terraces |
—
|
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: roof terraces | Statement: [Westgate Oxford, hasGreenFeatures, roof terraces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenFeatures Context triple: [Westgate Oxford, hasGreenFeatures, roof terraces]
-
A.
hasSustainabilityFeature
chosen
Indicates that an entity includes or is associated with a feature, attribute, or characteristic that contributes to environmental, social, or economic sustainability.
-
B.
hasGreenType
Indicates that an entity possesses or is associated with a type classified as green.
-
C.
hasVillageGreen
Indicates that one entity possesses or includes a village green as part of its area or facilities.
-
D.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
E.
hasGreenhouse
Indicates that an entity possesses or includes a greenhouse structure or facility.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c992fc8190bd262d528be0e636 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.