Triple
T10816754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanda Wasilewska |
E255250
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wasilewska |
E255250
|
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: Wasilewska | Statement: [Wanda Wasilewska, familyName, Wasilewska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wasilewska Context triple: [Wanda Wasilewska, familyName, Wasilewska]
-
A.
Wasilewska
chosen
Wasilewska is a Polish surname most notably associated with Wanda Wasilewska, a 20th-century Polish and Soviet writer and communist activist.
-
B.
Walewska
Walewska is a Polish surname most famously associated with Maria Walewska, a noblewoman known as the mistress of Napoleon Bonaparte.
-
C.
Leszczyńska
Leszczyńska is a Polish surname most famously borne by Marie Leszczyńska, Queen consort of France as the wife of King Louis XV.
-
D.
Zofia
Zofia is a feminine given name of Slavic origin, particularly common in Poland and other Central and Eastern European countries.
-
E.
Komorowska
Komorowska is a Polish surname borne by various notable individuals in Poland.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eea03c8190a68f4d4f89f497a2 |
completed | April 9, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e21649a6308190878432635d523686 |
completed | April 17, 2026, 11:15 a.m. |
Created at: April 8, 2026, 9:18 p.m.