Triple
T20042302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operant conditioning |
E497449
|
entity |
| Predicate | oftenRepresentedBy |
P54139
|
FINISHED |
| Object | cumulative recorder |
—
|
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: cumulative recorder | Statement: [Operant conditioning, oftenRepresentedBy, cumulative recorder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenRepresentedBy Context triple: [Operant conditioning, oftenRepresentedBy, cumulative recorder]
-
A.
areRepresentedBy
chosen
Indicates that one entity serves as a representation, proxy, or stand-in for another entity.
-
B.
primarilyRepresentedBy
Indicates that one entity serves as the main or most characteristic representation or depiction of another entity.
-
C.
representedByCharacter
Indicates that one entity is depicted, symbolized, or personified by a particular character in a work or medium.
-
D.
representsPeople
Indicates that one entity serves as a representation or stand-in for one or more people.
-
E.
representedFor
Indicates that one entity has acted or served as the official representative or proxy on behalf of another entity.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662ec9ae0819097032ff50d6215c2 |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:37 p.m.