Triple
T10276407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga Tokarczuk |
E240974
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Nowa Ruda |
E441697
|
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: Nowa Ruda | Statement: [Olga Tokarczuk, residence, Nowa Ruda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nowa Ruda Context triple: [Olga Tokarczuk, residence, Nowa Ruda]
-
A.
Nowa Ruda
chosen
Nowa Ruda is a town in southwestern Poland, in the Lower Silesian Voivodeship, known for its historical coal mining industry and picturesque setting in the Owl Mountains.
-
B.
Nowa Dęba
Nowa Dęba is a small town in southeastern Poland, known for its industrial traditions and location in the Subcarpathian Voivodeship.
-
C.
Mikołów
Mikołów is a historic town in southern Poland known for its traditional Silesian character and proximity to the regional capital, Katowice.
-
D.
Krasnystaw
Krasnystaw is a town in eastern Poland known for its agricultural surroundings and annual Chmielaki beer and hops festival.
-
E.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
- 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_69d6f82188588190998e06cad1e15e68 |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:37 a.m.