Triple
T29153961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humberg hill |
E738985
|
entity |
| Predicate | hasRecreationFunction |
P79548
|
FINISHED |
| Object | urban fringe green area |
—
|
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: urban fringe green area | Statement: [Humberg hill, hasRecreationFunction, urban fringe green area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecreationFunction Context triple: [Humberg hill, hasRecreationFunction, urban fringe green area]
-
A.
hasRecreationValue
Indicates that something provides opportunities or benefits for leisure, enjoyment, or recreational activities.
-
B.
hasRecreationContext
chosen
Indicates that an entity is associated with a recreational setting, purpose, or usage context.
-
C.
hasRecreationSetting
Indicates that an entity is associated with a particular type of recreational environment or setting in which recreational activities occur.
-
D.
hasRecreationType
Indicates that an entity is associated with or offers a particular type or category of recreational activity.
-
E.
hasRecreationSection
Indicates that an entity includes or is associated with a designated recreation section or recreational area.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
Created at: April 28, 2026, 11:43 a.m.