Triple
T7319875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Struma River |
E168510
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Sandanski |
E294571
|
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: Sandanski | Statement: [Struma River, passesThrough, Sandanski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandanski Context triple: [Struma River, passesThrough, Sandanski]
-
A.
Sandanski
chosen
Sandanski is a town in southwestern Bulgaria known as a spa and climatic resort in the Struma River valley near the Greek border.
-
B.
Varna
Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
-
C.
Smolyan
Smolyan is a Bulgarian town known as an administrative, cultural, and tourist center in the Rhodope Mountains.
-
D.
Dupnitsa
Dupnitsa is a town in southwestern Bulgaria known as a regional center near the Osogovo Mountains, with historical roots and access to mountain tourism and outdoor activities.
-
E.
Silistra
Silistra is a historic city in northeastern Bulgaria on the Danube River, known as an important cultural and economic center of the Dobruja region.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ef1a7a3c81909504eb711056f302 |
completed | March 27, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eefcd7148190818d581cbde9aff1 |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3:02 p.m.