Triple
T2084234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolokotrones University Professor at Harvard University |
E45311
|
entity |
| Predicate | typeOfEndowment |
P14891
|
FINISHED |
| Object | university 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: university professorship | Statement: [Kolokotrones University Professor at Harvard University, typeOfEndowment, university professorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfEndowment Context triple: [Kolokotrones University Professor at Harvard University, typeOfEndowment, university professorship]
-
A.
endowment
Indicates that a resource, asset, or benefit is provided or allocated to an entity, typically as a lasting or dedicated funding source.
-
B.
hasEndowmentType
chosen
Indicates that an entity is associated with a particular category or type of endowment.
-
C.
endowmentCurrency
Indicates the type of currency in which an endowment is denominated or valued.
-
D.
grantmakingType
Indicates the specific category or method by which grants are awarded or administered in a grantmaking relationship.
-
E.
funderType
Indicates the category or kind of organization or individual that provides funding in the relationship.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba524b60819089a11957ce6dbc4b |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b298a48190b4bdf7c9800b058d |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.