Triple
T20368181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Razlog |
E496971
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Bansko |
—
|
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: Bansko | Statement: [Razlog, locatedNear, Bansko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bansko Context triple: [Razlog, locatedNear, Bansko]
-
A.
Bansko
chosen
Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
-
B.
Sapareva Banya
Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
-
C.
Smolyan
Smolyan is a Bulgarian town known as an administrative, cultural, and tourist center in the Rhodope Mountains.
-
D.
Velbazhd
Velbazhd is the historical name of the Bulgarian town of Kyustendil, known as the site of a major medieval battle between Serbian and Bulgarian forces.
-
E.
Sliven
Sliven is a city in eastern Bulgaria known for its textile industry, historic role in Bulgarian national revival, and location near the eastern Balkan Mountains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678734b188190bb2c5863023f9f8c |
completed | April 20, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:26 a.m.