Triple
T24274396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherni Vrah |
E605365
|
entity |
| Predicate | countryCapitalVisible |
P155627
|
FINISHED |
| Object | Sofia |
—
|
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: Sofia | Statement: [Cherni Vrah, countryCapitalVisible, Sofia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCapitalVisible Context triple: [Cherni Vrah, countryCapitalVisible, Sofia]
-
A.
countryCapitalContext
Indicates that one entity serves as the capital city of the specified country in a given contextual or temporal setting.
-
B.
countryCapitalOverlooked
Indicates that a country's capital city is being neglected, ignored, or insufficiently recognized in a given context or consideration.
-
C.
countryCapitalOfSeat
Indicates that a country serves as the capital location or official seat of a specified entity, such as an organization or institution.
-
D.
countryCapitalRelation
Indicates that one entity is the capital city of the country represented by the other entity.
-
E.
countryCapitalMunicipality
Indicates that a given municipality serves as the capital city of a specified country.
- F. None of above. chosen
Provenance (4 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28d5da53c8190810f4e7777d112ba |
completed | April 29, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:07 a.m.