Triple
T11827793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vienna Prater |
E281300
|
entity |
| Predicate | hasOpeningPattern |
P17856
|
FINISHED |
| Object | public green areas open year‑round |
—
|
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: public green areas open year‑round | Statement: [Vienna Prater, hasOpeningPattern, public green areas open year‑round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningPattern Context triple: [Vienna Prater, hasOpeningPattern, public green areas open year‑round]
-
A.
hasOpeningType
chosen
Indicates that one entity has, features, or is characterized by a particular type or kind of opening.
-
B.
hasOpening
Indicates that one entity possesses or features an opening, gap, or entrance that allows access, passage, or exposure.
-
C.
hasOpeningCondition
Indicates that a relationship or action is subject to a specific initial condition that must be met before it can begin or take effect.
-
D.
hasOpeningSetting
Indicates that one entity (typically a narrative work) has its initial scene or setting located in the other entity.
-
E.
hasOpeningFunction
Indicates that an entity possesses a specific function or role related to opening something (e.g., access, initiation, or activation).
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ec3a148190bb184ba0d481b16a |
completed | April 10, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.