Triple
T7729797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stefan Czarniecki |
E175220
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Sokołówka |
E508209
|
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: Sokołówka | Statement: [Stefan Czarniecki, placeOfDeath, Sokołówka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sokołówka Context triple: [Stefan Czarniecki, placeOfDeath, Sokołówka]
-
A.
Sokołówka
chosen
Sokołówka is a small river in Poland known for flowing through the city of Łódź and its surrounding areas.
-
B.
Sokółka
Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
-
C.
Zawichost
Zawichost is a small historic town in southeastern Poland, situated on the Vistula River in the Świętokrzyskie Voivodeship.
-
D.
Chorkówka
Chorkówka is a village in southeastern Poland known historically as the place where pioneering oil industry chemist and pharmacist Ignacy Łukasiewicz spent his final years and died.
-
E.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703170650819095a1b073d67d231d |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce38b159d0819087efca6f80797971 |
completed | April 2, 2026, 9:36 a.m. |
Created at: March 27, 2026, 4:06 p.m.