Triple
T983301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blagoevgrad |
E21220
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Sofia |
E31299
|
NE 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: Sofia | Statement: [Blagoevgrad, roadConnection, Sofia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sofia Context triple: [Blagoevgrad, roadConnection, Sofia]
-
A.
Sofia
chosen
Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
-
B.
Varna
Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
-
C.
Ruse
Ruse is a major Bulgarian city and river port on the Danube, known for its elegant architecture and role as an important economic and transport hub.
-
D.
Bucharest
Bucharest is the capital and largest city of Romania, known for its mix of historic architecture, wide boulevards, and its role as the country’s political, cultural, and economic center.
-
E.
Belgrade
Belgrade is the capital and largest city of Serbia, historically significant as a strategic crossroads between Central Europe and the Balkans on the confluence of the Sava and Danube rivers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b493f5dc819090d239c2f7e083de |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ce14ffc8190b2d0a7915960ff89 |
completed | March 7, 2026, 12:41 p.m. |
Created at: March 1, 2026, 7:41 p.m.