Triple
T22673833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irina Slutskaya |
E560291
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Slutskaya |
—
|
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: Slutskaya | Statement: [Irina Slutskaya, familyName, Slutskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slutskaya Context triple: [Irina Slutskaya, familyName, Slutskaya]
-
A.
Slutsk
chosen
Slutsk is a historic town in central Belarus known for its role as a regional center and for its traditional Slutsk belts.
-
B.
Kobryn
Kobryn is a historic town in southwestern Belarus known for its location at the confluence of the Mukhavets and Dnieper–Bug Canal and its role as a regional cultural and economic center.
-
C.
Volnovakha
Volnovakha is a town in eastern Ukraine that serves as an important local administrative and transport hub within Donetsk Oblast.
-
D.
Mahilyowskaya
Mahilyowskaya is a metro station on the Minsk Metro system in Minsk, Belarus.
-
E.
Novoslobodskaya
Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178229e908190b696d14a93c11344 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:10 p.m.