Triple
T23720885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drawsko Pomorskie |
E586138
|
entity |
| Predicate | hasMilitaryTrainingAreaNearby |
P34345
|
FINISHED |
| Object | Drawsko Training Ground |
—
|
NE NERFINISHED |
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: Drawsko Training Ground | Statement: [Drawsko Pomorskie, hasMilitaryTrainingAreaNearby, Drawsko Training Ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryTrainingAreaNearby Context triple: [Drawsko Pomorskie, hasMilitaryTrainingAreaNearby, Drawsko Training Ground]
-
A.
hasNearbyMilitaryTrainingArea
chosen
Indicates that an entity is located close to a designated area used for military training activities.
-
B.
hasFormerMilitaryInstallationNearby
Indicates that an entity is located close to a site where a military installation previously existed but is no longer active.
-
C.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
D.
partOfMilitaryArea
Indicates that one entity is located within or belongs to a designated military-controlled area of another entity.
-
E.
hasNearbyMilitaryTown
Indicates that one location is situated close to a town whose primary function or identity is associated with military presence or activity.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b910759c8190be189db3e86d7258 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:01 p.m.