Triple
T19832127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Lydia |
E476487
|
entity |
| Predicate | genderRoleReversal |
P21356
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Queen of Lydia, genderRoleReversal, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderRoleReversal Context triple: [Queen of Lydia, genderRoleReversal, yes]
-
A.
genderReversalOf
chosen
Indicates that one entity is a counterpart of another with the same role or characteristics but with the opposite gender.
-
B.
hasGenderRole
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
-
C.
genderVariation
Indicates that one entity is a variant or alternative form of another entity that differs specifically in grammatical or biological gender.
-
D.
sexualRole
Indicates the specific sexual function, position, or behavioral role one entity assumes in a sexual interaction or relationship with another.
-
E.
genderNorms
Indicates socially constructed expectations or rules about how individuals should behave, appear, or identify based on their perceived gender.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ce68b48190aa25b29d0b6ea021 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.