Triple
T22219109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Snopes |
E549158
|
entity |
| Predicate | hasFictionalGender |
P92864
|
FINISHED |
| Object | female |
—
|
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 | Statement: [Linda Snopes, hasFictionalGender, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalGender Context triple: [Linda Snopes, hasFictionalGender, female]
-
A.
fictionalGender
chosen
Indicates that one entity has a gender identity or classification that exists only within a fictional or imaginary context.
-
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.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
D.
hasFictionalDemographic
Indicates that an entity is associated with a demographic group that is fictional or exists only within a created narrative or imagined context.
-
E.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
- 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_69e11e403d6481909a94d0aaf157f6ef |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b8edd288190a49f10e009122057 |
completed | April 28, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:37 p.m.