Triple
T17579782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvano |
E428169
|
entity |
| Predicate | typicalGenderInItaly |
P34349
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Silvano, typicalGenderInItaly, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGenderInItaly Context triple: [Silvano, typicalGenderInItaly, male]
-
A.
hasGenderInItalian
Indicates that an entity is associated with a specific grammatical gender when expressed in the Italian language.
-
B.
hasTypicalGenderAssociation
chosen
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
-
C.
genderOfResidents
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
D.
genderOfTypicalHolder
Indicates the gender that is most commonly associated with or typical of the usual holder of something.
-
E.
hasGenderInPolish
Indicates that an entity has a specific grammatical gender when expressed in the Polish language.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cc493c8190965680cf786aa531 |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.