Triple
T1847827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varna |
E41324
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Sea Capital of Bulgaria |
E41324
|
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: Sea Capital of Bulgaria | Statement: [Varna, hasNickname, Sea Capital of Bulgaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sea Capital of Bulgaria Context triple: [Varna, hasNickname, Sea Capital of Bulgaria]
-
A.
Pazardzhik, Bulgaria
Pazardzhik is a city in southern Bulgaria known as a regional administrative and cultural center on the banks of the Maritsa River.
-
B.
Burgas
Burgas is a major Bulgarian city and industrial center on the Black Sea coast, known for its large seaport and role as a key maritime and logistics hub in the region.
-
C.
Plovdiv
Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
-
D.
Varna
chosen
Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
-
E.
Blagoevgrad
Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb05412a08190855ea453d1264ea3 |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9c2e0a081909f521e6f73956239 |
completed | March 8, 2026, 7:10 p.m. |
Created at: March 4, 2026, 7:33 p.m.