Triple
T5830685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuck School of Business |
E129336
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Edward Tuck |
E580433
|
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: Edward Tuck | Statement: [Tuck School of Business, namedAfter, Edward Tuck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward Tuck Context triple: [Tuck School of Business, namedAfter, Edward Tuck]
-
A.
Edward Tuck
chosen
Edward Tuck was an American banker and philanthropist best known for endowing Dartmouth College’s graduate business school, which was named the Tuck School of Business in his honor.
-
B.
John Ternouth
John Ternouth was a 19th-century British sculptor best known for creating the bronze reliefs that adorn Nelson's Column in Trafalgar Square, London.
-
C.
Edward Talbot
Edward Talbot was an Anglican clergyman who became the inaugural Bishop of Southwark in the Church of England.
-
D.
Philip Latham
Philip Latham was a British actor best known for his character roles in film and television, particularly in period dramas.
-
E.
John L. Lumley
John L. Lumley was a prominent American fluid dynamicist known for his pioneering contributions to the understanding and modeling of turbulence.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0346ac31c8190bbd28444f75da875 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5189fa210819097ed10fd854d20b1 |
completed | March 26, 2026, 11:29 a.m. |
Created at: March 22, 2026, 3:54 p.m.