Triple
T37674684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collserola Natural Park |
E938058
|
entity |
| Predicate | isUrbanGreenLungOf |
P24628
|
FINISHED |
| Object | Barcelona metropolitan area |
—
|
NE NERFINISHED |
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: Barcelona metropolitan area | Statement: [Collserola Natural Park, isUrbanGreenLungOf, Barcelona metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanGreenLungOf Context triple: [Collserola Natural Park, isUrbanGreenLungOf, Barcelona metropolitan area]
-
A.
isUrbanOasisFor
Indicates a place serves as a refreshing, nature-rich retreat or sanctuary within an otherwise urban or heavily built-up environment for a given entity.
-
B.
isUrbanForest
chosen
Indicates that an area of trees and vegetation is located within or closely integrated with an urban or suburban environment.
-
C.
isUrbanOpenSpace
Indicates that a given area functions as an open, publicly accessible space within an urban environment.
-
D.
isUrbanPark
Indicates that a location is designated and used as a public park within an urban or metropolitan area.
-
E.
isUrbanLandmark
Indicates that a place or structure is recognized as a notable or significant landmark within an urban 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.