Triple
T26916595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleja Korfantego |
E677532
|
entity |
| Predicate | namedAfterEponymCitizenship |
P35759
|
FINISHED |
| Object | Polish |
—
|
LITERAL 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: Polish | Statement: [Aleja Korfantego, namedAfterEponymCitizenship, Polish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterEponymCitizenship Context triple: [Aleja Korfantego, namedAfterEponymCitizenship, Polish]
-
A.
hasEponymCitizenship
chosen
Indicates that an entity’s eponym (the person or figure it is named after) holds or held a particular citizenship or national affiliation.
-
B.
hasLaureateCitizenship
Indicates that a laureate holds or has held citizenship in a specified country or political entity.
-
C.
hasBiographicalSubjectCitizenship
Indicates that the biographical subject holds or has held citizenship in the specified country or political entity.
-
D.
eponymCountry
Indicates that a country is named after (or serves as the namesake for) a particular person, place, or entity.
-
E.
namedForNationalityOfHonouree
Indicates that something is named in honor of a person, specifically referencing that person's nationality.
- F. None of above.
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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 6:04 a.m.