Triple
T34841484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zlatograd–Thermes border crossing |
E1004351
|
entity |
| Predicate | nearbySettlementBG |
P182445
|
FINISHED |
| Object | Zlatograd |
—
|
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: Zlatograd | Statement: [Zlatograd–Thermes border crossing, nearbySettlementBG, Zlatograd]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbySettlementBG Context triple: [Zlatograd–Thermes border crossing, nearbySettlementBG, Zlatograd]
-
A.
nearVillageInBulgaria
chosen
Indicates that one entity is located close to a village situated within the country of Bulgaria.
-
B.
nearbyCityAlbania
Indicates that one city is geographically close to another city within Albania.
-
C.
nearCityInNorthMacedonia
Indicates that one entity is located close to a specified city within the country of North Macedonia.
-
D.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
E.
nearestTownSerbia
Indicates the relationship where a given location is associated with the geographically closest town within the territory of Serbia.
- 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4 p.m.