Triple
T32460144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifting as We Climb |
E829547
|
entity |
| Predicate | associatedWithGenderGroup |
P113101
|
FINISHED |
| Object | Black women |
—
|
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: Black women | Statement: [Lifting as We Climb, associatedWithGenderGroup, Black women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithGenderGroup Context triple: [Lifting as We Climb, associatedWithGenderGroup, Black women]
-
A.
hasTypicalGenderAssociation
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
-
B.
genderRoleAssociation
Indicates an association between a gender and a particular social role, behavior, or expectation.
-
C.
associatedWithCharacterGroup
Indicates that an entity has a connection or affiliation with a particular group of characters.
-
D.
genderOfMembers
chosen
Indicates the gender or genders associated with the members of a group or organization.
-
E.
genderCategoryIncludes
Indicates that a given gender category encompasses or contains the specified gender identity or subgroup.
- 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_69f3491df9288190afc0b23b1d6e72ce |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:57 a.m.