Triple
T5106075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ainsley |
E115096
|
entity |
| Predicate | hasAttitudeToward |
P27747
|
FINISHED |
| Object | gender roles |
—
|
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: gender roles | Statement: [Ainsley, hasAttitudeToward, gender roles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttitudeToward Context triple: [Ainsley, hasAttitudeToward, gender roles]
-
A.
hasUserAttitude
chosen
Indicates that one entity holds a particular attitude, opinion, or evaluative stance toward another entity or subject.
-
B.
attitudeToRa’y
Indicates the nature or stance of one entity’s attitude, opinion, or feeling toward Ra’y.
-
C.
hasOppositionalPerception
Indicates that one entity perceives another entity, concept, or situation as being in opposition, conflict, or contradiction to itself or its interests.
-
D.
hasSentiment
Indicates that one entity expresses or embodies a particular emotional attitude, evaluation, or sentiment toward another entity or subject.
-
E.
hasTendency
Indicates that an entity is inclined or likely to exhibit a particular behavior, characteristic, or outcome under certain conditions.
- 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75a7c6748190b02b7c2b617c830f |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.