Triple
T4285939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sitia |
E97267
|
entity |
| Predicate | hasNearbyNaturalArea |
P33602
|
FINISHED |
| Object | Vai palm forest |
—
|
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: Vai palm forest | Statement: [Sitia, hasNearbyNaturalArea, Vai palm forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyNaturalArea Context triple: [Sitia, hasNearbyNaturalArea, Vai palm forest]
-
A.
hasNearbyNatureReserve
Indicates that one place or entity is located close to a designated nature reserve.
-
B.
hasNearbyWildernessArea
Indicates that a wilderness area is located within a close geographic proximity to the referenced place or entity.
-
C.
hasNearbyStatePark
Indicates that a location is situated close to at least one designated state park.
-
D.
hasNearbyGreenSpace
chosen
Indicates that an entity is located close to an area of green space, such as a park, garden, or natural vegetation.
-
E.
containsNaturalPark
Indicates that one entity geographically includes or encompasses a natural park within its boundaries.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3505d23d88190a638f2cc2acee9ee |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.