Triple
T16144482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cripps family |
E391742
|
entity |
| Predicate | knownForDonationType |
P54536
|
FINISHED |
| Object | endowments to universities |
—
|
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: endowments to universities | Statement: [Cripps family, knownForDonationType, endowments to universities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForDonationType Context triple: [Cripps family, knownForDonationType, endowments to universities]
-
A.
typeOfDonations
chosen
Indicates the kinds or categories of donations involved in a given context or transaction.
-
B.
donatedWith
Indicates that an entity made a donation using, accompanied by, or in association with a particular method, item, or context.
-
C.
notableDonor
Indicates that one entity is a significant or prominent donor to another entity, typically through substantial or noteworthy contributions.
-
D.
recognizesContributionType
Indicates that an entity acknowledges or identifies a specific type or category of contribution made by another entity.
-
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.
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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d92b0408190a010bd8e5193aa36 |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.