Triple
T5646382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raisa Gorbacheva |
E124393
|
entity |
| Predicate | maidenName |
P18
|
FINISHED |
| Object | Titarenko |
E486136
|
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: Titarenko | Statement: [Raisa Gorbacheva, maidenName, Titarenko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Titarenko Context triple: [Raisa Gorbacheva, maidenName, Titarenko]
-
A.
Titarenko
chosen
Titarenko is a Ukrainian-origin surname most notably borne by Raisa Maksimovna, the wife of former Soviet leader Mikhail Gorbachev.
-
B.
Turchynov
Turchynov is a Ukrainian politician and former acting president of Ukraine known for his roles in the country’s post-2014 political transition.
-
C.
Turek
Turek is a town in central Poland known historically for its textile industry and its location in the Greater Poland region.
-
D.
Tupikov
Tupikov is a Russian surname most notably associated with Vasiliy Tupikov, a Soviet military figure.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022aa650c819088d9046b82fab631 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d84e14c8190b913486cb516eee1 |
completed | March 22, 2026, 8:13 p.m. |
Created at: March 22, 2026, 3:41 p.m.