Triple
T365266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morton D. Hull Distinguished Service Professor |
E7945
|
entity |
| Predicate | endowmentType |
P930
|
FINISHED |
| Object | distinguished service professorship |
—
|
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: distinguished service professorship | Statement: [Morton D. Hull Distinguished Service Professor, endowmentType, distinguished service professorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endowmentType Context triple: [Morton D. Hull Distinguished Service Professor, endowmentType, distinguished service professorship]
-
A.
endowment
chosen
Indicates that a resource, asset, or benefit is provided or allocated to an entity, typically as a lasting or dedicated funding source.
-
B.
endowmentCurrency
Indicates the type of currency in which an endowment is denominated or valued.
-
C.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
D.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
E.
dividendType
Indicates the classification of a dividend based on its nature or form (e.g., cash, stock, special), specifying what kind of dividend is being distributed.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe6c1b4819083335e880c205ed6 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.