Triple
T17178281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korneliya Ninova |
E416916
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Korneliya |
E416916
|
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: Korneliya | Statement: [Korneliya Ninova, givenName, Korneliya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korneliya Context triple: [Korneliya Ninova, givenName, Korneliya]
-
A.
Ekaterina Gradova
Ekaterina Gradova was a Soviet and Russian actress best known for her roles in popular 1970s film and television productions.
-
B.
Dimitrova
Dimitrova is a common Bulgarian feminine surname derived from the masculine form Dimitrov.
-
C.
Korneliya Ninova
chosen
Korneliya Ninova is a Bulgarian politician and lawyer who has led the Bulgarian Socialist Party and served as a prominent figure in the country’s left-wing politics.
-
D.
Vladimira
Vladimira is a feminine given name, primarily used in Slavic cultures, derived from the male name Vladimir.
-
E.
Albena
Albena is a modern Black Sea coastal resort in northeastern Bulgaria, known for its long sandy beach, family-friendly hotels, and recreational facilities.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0ee5008190a73875b39841fd9f |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fca04cc8190a9df230078fbe268 |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:37 a.m.