Triple
T38630383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prestvannet |
E937433
|
entity |
| Predicate | hasRecreationalUseInSummer |
P80753
|
FINISHED |
| Object | birdwatching |
—
|
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: birdwatching | Statement: [Prestvannet, hasRecreationalUseInSummer, birdwatching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecreationalUseInSummer Context triple: [Prestvannet, hasRecreationalUseInSummer, birdwatching]
-
A.
hasRecreationalUseNearby
Indicates that there is at least one location or facility for recreational activities situated close to the referenced entity.
-
B.
hasRecreationalAspect
Indicates that something includes, involves, or is characterized by a recreational or leisure-related component or purpose.
-
C.
hasRecreationalUseRestriction
Indicates that there is a limitation or prohibition on how an entity may be used for recreational purposes.
-
D.
hasRecreationPurpose
chosen
Indicates that something is used or intended to be used for recreational or leisure activities.
-
E.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.