Triple
T25947220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sveti Vlas |
E653871
|
entity |
| Predicate | distanceToNessebar |
P192421
|
FINISHED |
| Object | approximately 10 km |
—
|
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: approximately 10 km | Statement: [Sveti Vlas, distanceToNessebar, approximately 10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNessebar Context triple: [Sveti Vlas, distanceToNessebar, approximately 10 km]
-
A.
distanceToBurgas_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Burgas.
-
B.
distanceToBansko
Indicates the measured distance between a given location or object and the place named Bansko.
-
C.
distanceToPlovdiv
Indicates the spatial distance between a given entity and the city of Plovdiv.
-
D.
distanceFromBlagoevgrad
Indicates the physical distance between a given entity or location and the city of Blagoevgrad.
-
E.
distanceFromVarna
Indicates the measured or specified distance between a given entity and the location Varna.
- 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_69e7ab40ac788190a771bc499eb1ae5f |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
| PDg | Predicate description generation | batch_69fd0b92150881909b1166fe6d09aa19 |
completed | May 7, 2026, 10 p.m. |
Created at: April 22, 2026, 8:43 a.m.