Triple
T32363891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ***Flawless |
E826936
|
entity |
| Predicate | hasFeministMessage |
P179224
|
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: [***Flawless, hasFeministMessage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeministMessage Context triple: [***Flawless, hasFeministMessage, yes]
-
A.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
B.
hasFemaleSpeaker
Indicates that the associated content, event, or communication is spoken or narrated by a female individual.
-
C.
hasSocialMessage
chosen
Indicates that something conveys, promotes, or is associated with a broader social, ethical, or political message.
-
D.
hasFemaleRecipients
Indicates that the subject entity has one or more recipients who are female.
-
E.
hasMoralMessage
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: May 1, 2026, 12:50 a.m.