Triple
T10276368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga Tokarczuk |
E240974
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Olga |
E136344
|
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: Olga | Statement: [Olga Tokarczuk, givenName, Olga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olga Context triple: [Olga Tokarczuk, givenName, Olga]
-
A.
Olga
Olga is a lingerie and intimate apparel brand owned by PVH Corp., known for designing comfortable, supportive undergarments for women.
-
B.
Olga
chosen
Olga is a female given name of Russian origin, historically borne by several notable figures including Russian grand duchesses and saints.
-
C.
Galina
Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
D.
Olga Lysova
Olga Lysova is a Russian woman best known as the first wife of billionaire businessman and former Chelsea F.C. owner Roman Abramovich.
-
E.
Lyudmila
Lyudmila is a common Russian female given name, notably borne by figures such as Soviet World War II sniper Lyudmila Pavlichenko.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d28c3b10819093cdab1392384dd4 |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794b9b1d881908c55aa50da68ae75 |
completed | April 9, 2026, 11:59 a.m. |
Created at: April 6, 2026, 11:37 a.m.