Triple
T12767671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Slovenia |
E305165
|
entity |
| Predicate | genderOfCurrentIncumbent |
P33965
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [President of Slovenia, genderOfCurrentIncumbent, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfCurrentIncumbent Context triple: [President of Slovenia, genderOfCurrentIncumbent, female]
-
A.
incumbentGender
chosen
Indicates the gender of the person currently holding a particular position or office.
-
B.
officeHoldersGenderEligibility
Indicates the gender-based criteria that determine who is eligible to hold a particular office or position.
-
C.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
-
D.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
E.
genderOfFirstHolder
Indicates that the relationship specifies the gender of the first entity that holds or possesses something in the described context.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df3b2f88190b37b696400178795 |
completed | April 10, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.