Triple
T25649699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicky Cornell |
E643064
|
entity |
| Predicate | activityAfter2017 |
P117527
|
FINISHED |
| Object | increased philanthropic engagement |
—
|
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: increased philanthropic engagement | Statement: [Vicky Cornell, activityAfter2017, increased philanthropic engagement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activityAfter2017 Context triple: [Vicky Cornell, activityAfter2017, increased philanthropic engagement]
-
A.
statusAfter2017
Indicates the status or condition an entity has specifically after the year 2017.
-
B.
modernActivities
Indicates that the associated activities are contemporary or characteristic of the modern era, as opposed to traditional or historical practices.
-
C.
has activity
Indicates that one entity performs, exhibits, or is engaged in a particular action, behavior, or process associated with another entity.
-
D.
statusAfter2018
Indicates the condition or state of something specifically during the period after the year 2018.
-
E.
hasEvidenceOfActivitySince
chosen
Indicates that there is evidence showing an entity has been active or engaged in some activity from a specified point in time onward.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 21, 2026, 6:19 p.m.