Triple
T21764158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Albert experiment |
E537234
|
entity |
| Predicate | unconditionedStimulus |
P139164
|
FINISHED |
| Object | loud noise |
—
|
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: loud noise | Statement: [Little Albert experiment, unconditionedStimulus, loud noise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unconditionedStimulus Context triple: [Little Albert experiment, unconditionedStimulus, loud noise]
-
A.
unconditionedStimulusExample
chosen
Indicates that one entity serves as an example of an unconditioned stimulus that naturally and automatically elicits a response without prior learning.
-
B.
conditionedStimulusExample
Indicates that something serves as an example of a conditioned stimulus, illustrating a stimulus that has acquired a response through associative learning.
-
C.
triggered
Indicates that one entity causes an event, action, or process involving another entity to start or occur.
-
D.
trigger
Indicates that one entity causes or initiates an event, state, or action in another entity or system.
-
E.
neutralized
Indicates that one entity has rendered another entity ineffective, harmless, or no longer able to exert its intended effect.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031a8a7f08190a4e50ebc24219585 |
completed | April 28, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:51 p.m.