Triple
T16329698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miedziowi |
E396516
|
entity |
| Predicate | hasGenderInPolish |
P122980
|
FINISHED |
| Object | masculine personal plural |
—
|
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: masculine personal plural | Statement: [Miedziowi, hasGenderInPolish, masculine personal plural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderInPolish Context triple: [Miedziowi, hasGenderInPolish, masculine personal plural]
-
A.
hasGenderInPortuguese
Indicates that a term or entity is associated with a specific grammatical gender in the Portuguese language.
-
B.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
C.
hasGenderInRussian
Indicates that an entity is associated with a specific grammatical gender in the Russian language.
-
D.
hasGenderInItalian
Indicates that an entity is associated with a specific grammatical gender when expressed in the Italian language.
-
E.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
- F. None of above. chosen
Provenance (4 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4debef08190a64f13214bfa098f |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.