Triple
T6982031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikołaj |
E161869
|
entity |
| Predicate | usedInCountry |
P715
|
FINISHED |
| Object | Poland |
E5029
|
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: Poland | Statement: [Mikołaj, usedInCountry, Poland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poland Context triple: [Mikołaj, usedInCountry, Poland]
-
A.
Poland
chosen
Poland is a Central European country known for its rich medieval heritage, resilient culture, and pivotal role in 20th-century history, including being the site of the outbreak of World War II.
-
B.
Polonia
Polonia refers to the global community of people of Polish origin living outside Poland, encompassing their cultural, social, and political organizations worldwide.
-
C.
Polón
Polón is a Finnish surname most notably associated with Eduard Polón, an industrialist and co-founder of the company that became part of Nokia.
-
D.
Poland and Czech Republic
Poland and the Czech Republic are neighboring Central European countries known for their shared history, cultural ties, and extensive cross-border rail connections.
-
E.
Poland and Germany
Poland and Germany are neighboring Central European countries with deep historical ties and extensive cross-border economic, cultural, and transportation connections.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db6d3f3c8190b0121f7934440c34 |
completed | March 27, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761bb90f48190882a58c2da10b3e4 |
completed | March 28, 2026, 5:06 a.m. |
Created at: March 27, 2026, 2:31 p.m.