Triple
T7884696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stenimachos |
E183072
|
entity |
| Predicate | presentDayName |
P11890
|
FINISHED |
| Object | Asenovgrad |
E476708
|
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: Asenovgrad | Statement: [Stenimachos, presentDayName, Asenovgrad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asenovgrad Context triple: [Stenimachos, presentDayName, Asenovgrad]
-
A.
Asenovgrad
chosen
Asenovgrad is a town in southern Bulgaria known as a gateway to the Rhodope Mountains and a regional center rich in historical and religious landmarks.
-
B.
Targovishte
Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
-
C.
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.
-
D.
Shumen
Shumen is a city in northeastern Bulgaria known for its historical significance, including nearby medieval capitals and the Monument to 1300 Years of Bulgaria.
-
E.
Gabrovo
Gabrovo is a town in central Bulgaria known for its humor and satire traditions, as well as its historical role in the country’s industrial development.
- 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_69ca828af6e48190a06ee7010d8f0e64 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39d62a148190bed4e0d199aa427b |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b9286c881909ec01cb899e71d42 |
completed | March 31, 2026, 5:28 a.m. |
Created at: March 30, 2026, 4:59 p.m.