Triple
T6231089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cunningham |
E139353
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | John W. Cunningham |
E310575
|
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: John W. Cunningham | Statement: [Cunningham, hasNotableBearer, John W. Cunningham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John W. Cunningham Context triple: [Cunningham, hasNotableBearer, John W. Cunningham]
-
A.
John W. Cunningham
chosen
John W. Cunningham was an American Western author best known for writing the short story that inspired the classic film "High Noon."
-
B.
Jack L. Murray
Jack L. Murray is a film producer best known for his work on the 2009 horror remake "My Bloody Valentine 3D."
-
C.
John Cummings
John Cummings is a Scottish musician best known as a former guitarist of the post-rock band Mogwai.
-
D.
James L. Massey
James L. Massey was an American information theorist and cryptographer known for his fundamental contributions to coding theory, stream ciphers, and the development of the Berlekamp–Massey algorithm.
-
E.
Hugh Roy Cullen
Hugh Roy Cullen was a prominent Texas oilman and philanthropist who became one of the leading benefactors of the University of Houston and other educational and medical institutions.
- 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ec5be4819084d6df2e8dd2a542 |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c673f2327481908f541d4b2095c958 |
completed | March 27, 2026, 12:11 p.m. |
Created at: March 22, 2026, 4:22 p.m.