Triple
T3133871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vassar College |
E65480
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Matthew Vassar |
E330583
|
NE 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: Matthew Vassar | Statement: [Vassar College, namedAfter, Matthew Vassar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Vassar Context triple: [Vassar College, namedAfter, Matthew Vassar]
-
A.
Matthew Vassar
chosen
Matthew Vassar was a 19th-century American businessman and philanthropist best known for establishing Vassar College, one of the first higher-education institutions for women in the United States.
-
B.
John Byron Diman
John Byron Diman was an American Episcopal clergyman and educator best known for establishing several prominent New England preparatory schools in the late 19th and early 20th centuries.
-
C.
Matthew Holworthy
Matthew Holworthy was a 17th-century English merchant and philanthropist best known for endowing the Holworthy Professorship of English Law at the University of Cambridge.
-
D.
Stilson Hutchins
Stilson Hutchins was an American newspaper publisher best known as the founder of The Washington Post.
-
E.
Gene Milford
Gene Milford was an American film editor known for his work on numerous classic Hollywood films across several decades.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada56104ec8190a14591ed73f3fe83 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235b2aa388190ae9dc569b951206d |
completed | March 12, 2026, 3:40 a.m. |
Created at: March 8, 2026, 3:05 p.m.