Triple
T9938487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kielce |
E194016
|
entity |
| Predicate | hasForestAreaNearby |
P44059
|
FINISHED |
| Object | Świętokrzyski National Park vicinity |
—
|
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: Świętokrzyski National Park vicinity | Statement: [Kielce, hasForestAreaNearby, Świętokrzyski National Park vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForestAreaNearby Context triple: [Kielce, hasForestAreaNearby, Świętokrzyski National Park vicinity]
-
A.
hasNearbyWildernessArea
Indicates that a wilderness area is located within a close geographic proximity to the referenced place or entity.
-
B.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
C.
hasNearbyNatureReserve
Indicates that one place or entity is located close to a designated nature reserve.
-
D.
nearNationalForest
chosen
Indicates that one entity is located close to, but not necessarily inside, a designated national forest area.
-
E.
hasNearbyPublicLand
Indicates that one entity is located close to an area of public land, such as parks, reserves, or other publicly accessible open spaces.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e64760819094f599f158d32f33 |
completed | April 2, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.