Triple
T20196127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pavlovian conditioning |
E493089
|
entity |
| Predicate | conditionedStimulusExample |
P139165
|
FINISHED |
| Object | bell sound |
—
|
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: bell sound | Statement: [Pavlovian conditioning, conditionedStimulusExample, bell sound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionedStimulusExample Context triple: [Pavlovian conditioning, conditionedStimulusExample, bell sound]
-
A.
extraExample
Indicates that something is provided as an additional, illustrative instance beyond the main or required examples.
-
B.
centralExample
Indicates that one entity serves as the primary or most representative example of another entity or concept.
-
C.
mechanismExample
Indicates that one entity serves as an illustrative example of the mechanism or process by which another entity operates or produces an effect.
-
D.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
E.
valueExample
Indicates that something is provided as an illustrative or sample instance of a particular value.
- F. None of above. chosen
Provenance (4 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad8b3cc8190aa9c9c79c552002a |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:37 p.m.