Triple
T14505518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yelena Bonner |
E340254
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Yelena |
E226393
|
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: Yelena | Statement: [Yelena Bonner, givenName, Yelena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yelena Context triple: [Yelena Bonner, givenName, Yelena]
-
A.
Yelena
chosen
Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
-
B.
Natalya
Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
-
C.
Katusha Maslova
Katusha Maslova is a central fictional character in Leo Tolstoy’s novel "Resurrection," whose life story explores themes of moral redemption and social injustice in late 19th-century Russia.
-
D.
Irina
Irina is a feminine given name commonly used in Slavic and other Eastern European cultures, derived from the Greek name Irene meaning "peace."
-
E.
Yelena Yemchuk
Yelena Yemchuk is a Ukrainian-American photographer, painter, and film director known for her surreal, dreamlike imagery and collaborations with fashion brands and musicians.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e25a2481908b8394e9a19f3b64 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6da07ff481909fb2463b0ea92849 |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:21 a.m.