Triple
T975815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Science and Human Behavior |
E21049
|
entity |
| Predicate | hasAuthorialSchool |
P15584
|
FINISHED |
| Object | radical behaviorism |
—
|
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: radical behaviorism | Statement: [Science and Human Behavior, hasAuthorialSchool, radical behaviorism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorialSchool Context triple: [Science and Human Behavior, hasAuthorialSchool, radical behaviorism]
-
A.
hasArtisticSchool
chosen
Indicates that an entity is associated with, belongs to, or is characterized by a particular artistic school or style.
-
B.
hasHistoricalWritingInfluenceFrom
Indicates that one entity’s historical writing style, content, or traditions are influenced by those of another entity.
-
C.
hasAuthor
Indicates that an entity is written or created by a specific author.
-
D.
traditionalAuthorship
Indicates that an entity is recognized as the conventional or historically accepted author of a work, according to traditional attribution.
-
E.
hasInfluentialGrammarian
Indicates that an entity is associated with, or characterized by, a grammarian who has significant influence or authority in matters of grammar.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46234c88190b2bfc9cafe59d7f7 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.