Triple
T24409990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | theory of cognitive dissonance |
E615420
|
entity |
| Predicate | hasKeyPhenomenon |
P137709
|
FINISHED |
| Object | induced compliance |
—
|
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: induced compliance | Statement: [theory of cognitive dissonance, hasKeyPhenomenon, induced compliance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyPhenomenon Context triple: [theory of cognitive dissonance, hasKeyPhenomenon, induced compliance]
-
A.
hasAssociatedPhenomenon
chosen
Indicates that one entity is linked to, or typically occurs together with, a particular phenomenon or observable event.
-
B.
hasKeyNotion
Indicates that one entity embodies or contains a central or fundamental concept relevant to another entity.
-
C.
capturesPhenomenon
Indicates that one entity records, represents, or effectively reflects the occurrence or characteristics of a particular phenomenon.
-
D.
hasKeyAccord
Indicates that one entity possesses or defines the primary key or governing agreement that authorizes or controls another entity.
-
E.
examplePhenomenon
Indicates a representative or illustrative occurrence used to demonstrate or clarify a broader phenomenon or pattern.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2958076a88190880feb3ea6c0abf1 |
completed | April 29, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.