Triple
T31835780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ninshubur |
E812667
|
entity |
| Predicate | genderInSomeLaterTraditions |
P20413
|
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: [Ninshubur, genderInSomeLaterTraditions, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderInSomeLaterTraditions Context triple: [Ninshubur, genderInSomeLaterTraditions, male]
-
A.
hasGenderInSomeTraditions
chosen
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
B.
hasGenderDivisions
Indicates that something is organized, classified, or separated into groups based on gender.
-
C.
equatedWithInSomeTraditions
Indicates that, in certain cultural, religious, or scholarly traditions, one entity is regarded as equivalent to or identified with another.
-
D.
hasGenderConvention
Indicates that there is an established or customary way of assigning or expressing gender within a given context, system, or culture.
-
E.
priesthoodGender
Indicates the gender associated with a particular priesthood role or office.
- 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_69f348ea7ffc8190a2ab43d80277cf59 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 30, 2026, 11:48 p.m.