Triple
T34859491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tripoint of Bulgaria–Greece–Turkey |
E1004825
|
entity |
| Predicate | nearVillageInTurkey |
P181929
|
FINISHED |
| Object | Bosnaköy |
—
|
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: Bosnaköy | Statement: [tripoint of Bulgaria–Greece–Turkey, nearVillageInTurkey, Bosnaköy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearVillageInTurkey Context triple: [tripoint of Bulgaria–Greece–Turkey, nearVillageInTurkey, Bosnaköy]
-
A.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
B.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
C.
nearestTouristDestination
Indicates that one location is the closest tourist destination to another specified location.
-
D.
nearbyCityAlbania
Indicates that one city is geographically close to another city within Albania.
-
E.
nearCityInSyria
Indicates that one entity is located close to a specified city within the country of Syria.
- F. None of above. chosen
Provenance (4 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f782f416c081908bdd9b1ad456f0e2 |
completed | May 3, 2026, 5:16 p.m. |
Created at: May 3, 2026, 4 p.m.