Triple
T13473880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Binney |
E318197
|
entity |
| Predicate | existenceContext |
P36
|
FINISHED |
| Object | protagonist’s imagination |
—
|
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: protagonist’s imagination | Statement: [Mark Binney, existenceContext, protagonist’s imagination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: existenceContext Context triple: [Mark Binney, existenceContext, protagonist’s imagination]
-
A.
contextOf
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
B.
contextType
Indicates the type or category of contextual information associated with an entity or event.
-
C.
context
chosen
Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
-
D.
acquisitionContext
Indicates the circumstances, conditions, or setting under which an acquisition or purchase takes place.
-
E.
contextHolds
Indicates that a particular contextual condition or situation is valid and in effect for the related entities or statements.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2447bc81908baf1f4b55095144 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.