Triple
T9758456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sobekneferu |
E236609
|
entity |
| Predicate | usedBothMaleAndFemaleRegalia |
P90845
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sobekneferu, usedBothMaleAndFemaleRegalia, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedBothMaleAndFemaleRegalia Context triple: [Sobekneferu, usedBothMaleAndFemaleRegalia, true]
-
A.
hasGenderInSomeTraditions
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
B.
relatedRegalia
Indicates that there is an association or connection between items of regalia, such as ceremonial garments, insignia, or symbols of office.
-
C.
usesImperialRegalia
Indicates that one entity employs or incorporates imperial regalia (such as crowns, scepters, or other sovereign insignia) in relation to another entity or context.
-
D.
isUnisexInSomeRegions
Indicates that the item or concept is considered suitable or applicable to all genders, but only in certain geographic or cultural regions.
-
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_69ca84d64f6c8190a4ed4e9f5936eda5 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda047d0408190b91f7195513da6e8 |
completed | April 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69cd03d0772c8190bd1750cf1cfba309 |
completed | April 1, 2026, 11:38 a.m. |
| PDg | Predicate description generation | batch_69cd081a9c5c819093439be7e802ff85 |
completed | April 1, 2026, 11:57 a.m. |
Created at: March 30, 2026, 8:24 p.m.