Triple
T8142770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summer’s Day |
E190135
|
entity |
| Predicate | hasGenderPerspective |
P55521
|
FINISHED |
| Object | female gaze |
—
|
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 gaze | Statement: [Summer’s Day, hasGenderPerspective, female gaze]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderPerspective Context triple: [Summer’s Day, hasGenderPerspective, female gaze]
-
A.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
B.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
C.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
D.
hasGenderRole
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
-
E.
hasGenderInterpretation
chosen
Indicates that an entity is associated with a particular interpretation or understanding of 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4443a3748190bbae79f1d673c03d |
completed | March 31, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:36 p.m.