Triple
T19600983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philonous |
E470473
|
entity |
| Predicate | influencesReceptionOf |
P22974
|
FINISHED |
| Object | Berkeley’s immaterialist philosophy |
—
|
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: Berkeley’s immaterialist philosophy | Statement: [Philonous, influencesReceptionOf, Berkeley’s immaterialist philosophy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesReceptionOf Context triple: [Philonous, influencesReceptionOf, Berkeley’s immaterialist philosophy]
-
A.
influencedPerceptionOf
chosen
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
influencesPractice
Indicates that one entity affects, shapes, or alters the way another entity carries out its activities, methods, or customary behavior.
-
C.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
D.
influencedDiscussionOf
Indicates that one entity had an effect on the way another entity was discussed, framed, or debated.
-
E.
portrayalReception
Indicates how a particular portrayal of someone or something is received, evaluated, or responded to by an audience or observers.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407df98c8190b258ac3b690fe4b1 |
completed | April 20, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69e514e166dc8190a0f147e0b4c8bbe7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.