Triple
T69939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vincent Astor |
E1398
|
entity |
| Predicate | genreOfPhilanthropy |
P3801
|
FINISHED |
| Object | urban renewal in New York City |
—
|
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: urban renewal in New York City | Statement: [Vincent Astor, genreOfPhilanthropy, urban renewal in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfPhilanthropy Context triple: [Vincent Astor, genreOfPhilanthropy, urban renewal in New York City]
-
A.
partnerInPhilanthropy
Indicates a relationship where two or more entities collaborate as partners in philanthropic activities, initiatives, or charitable efforts.
-
B.
nonprofitStatus
Indicates that an entity operates as a nonprofit organization, typically meeting legal or regulatory criteria for nonprofit status.
-
C.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or activity.
-
D.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
E.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24fcf5a88819088c5fa4c08476358 |
completed | Feb. 28, 2026, 2:15 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.