Triple
T33699665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth |
E863418
|
entity |
| Predicate | centralEventInvolving |
P93648
|
FINISHED |
| Object | planned dinner with ex‑wife and lover |
—
|
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: planned dinner with ex‑wife and lover | Statement: [Kenneth, centralEventInvolving, planned dinner with ex‑wife and lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralEventInvolving Context triple: [Kenneth, centralEventInvolving, planned dinner with ex‑wife and lover]
-
A.
significantEventInvolves
chosen
Indicates that a significant event includes or engages a particular entity as a participant or key element.
-
B.
incidentWith
Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another entity.
-
C.
isMajorEventOf
Indicates that an event is a primary, significant, or defining occurrence within the context of another entity (such as a project, period, or process).
-
D.
centralIn
Indicates that one entity occupies a central or most important position within another entity, context, or structure.
-
E.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: May 1, 2026, 1:43 a.m.