Triple
T24129627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza de San Andrés |
E597907
|
entity |
| Predicate | hasGreenElements |
P24953
|
FINISHED |
| Object | ornamental trees |
—
|
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: ornamental trees | Statement: [Plaza de San Andrés, hasGreenElements, ornamental trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenElements Context triple: [Plaza de San Andrés, hasGreenElements, ornamental trees]
-
A.
hasGreenType
chosen
Indicates that an entity possesses or is associated with a type classified as green.
-
B.
hasGreenRuns
Indicates that an entity possesses or includes ski runs that are classified as green (i.e., beginner-level).
-
C.
hasGreenCar
Indicates that an entity possesses or owns a car that is green in color.
-
D.
hasGreenCorridorFunction
Indicates that something serves as a green corridor, enabling ecological connectivity or movement of species between natural or semi-natural areas.
-
E.
hasMainElements
Indicates that something possesses or is composed of its primary or most important constituent parts.
- 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_69e288c808b881909fed7d18f04bcbbe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1df7644808190b4bbbf4db1539f48 |
completed | April 29, 2026, 10:37 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:23 p.m.