Triple
T24062870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Switch (1991 film) |
E596000
|
entity |
| Predicate | hasGenderTransformationElement |
P154709
|
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: [Switch (1991 film), hasGenderTransformationElement, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderTransformationElement Context triple: [Switch (1991 film), hasGenderTransformationElement, true]
-
A.
hasIncarnationsOfGender
Indicates that an entity has different incarnations or forms that each express or are associated with a particular gender.
-
B.
genderReversalOf
Indicates that one entity is a counterpart of another with the same role or characteristics but with the opposite gender.
-
C.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
-
D.
hasAgeTransformation
Indicates a relationship where an entity undergoes or causes a change in age or age-related state.
-
E.
hasGenderRole
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da5825548190b94cb6e708617a7d |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:39 p.m.