Triple
T10758947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margot Birmingham Perot |
E253772
|
entity |
| Predicate | areaOfCharitableActivity |
P95822
|
FINISHED |
| Object | health care |
—
|
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: health care | Statement: [Margot Birmingham Perot, areaOfCharitableActivity, health care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaOfCharitableActivity Context triple: [Margot Birmingham Perot, areaOfCharitableActivity, health care]
-
A.
hasCharitableFunction
Indicates that an entity performs or is designated to perform activities intended for charitable purposes or public benefit.
-
B.
associatedCharity
Indicates that one entity has a formal or recognized charitable affiliation or partnership with another entity.
-
C.
isCharityEvent
Indicates that an event is organized primarily for charitable purposes, such as raising funds or awareness for a cause.
-
D.
hasCharitableFoundation
Indicates that an entity maintains or is associated with a charitable foundation, typically for philanthropic or nonprofit activities.
-
E.
philanthropicDonation
Indicates that one entity voluntarily gives money, goods, or services to another entity for charitable or public-benefit purposes without expecting direct compensation.
- F. None of above. chosen
Provenance (4 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d72ea21c5081908babc049d0330a75 |
completed | April 9, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.