Triple
T20919601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cullom Act |
E515169
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Shelby M. Cullom |
—
|
NE NERFINISHED |
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: Shelby M. Cullom | Statement: [Cullom Act, namedAfter, Shelby M. Cullom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shelby M. Cullom Context triple: [Cullom Act, namedAfter, Shelby M. Cullom]
-
A.
Shelby Moore Cullom
chosen
Shelby Moore Cullom was an American politician who served as governor of Illinois and later as a long-serving U.S. senator in the late 19th and early 20th centuries.
-
B.
Donna W. Scott
Donna W. Scott is an American actress and former model best known for her work in film and television and for being married to late director Tony Scott.
-
C.
Laurie S. Fulton
Laurie S. Fulton is an American attorney and diplomat who served as U.S. Ambassador to Denmark from 2009 to 2013.
-
D.
Terilyn A. Shropshire
Terilyn A. Shropshire is an American film editor known for her work on numerous acclaimed films and television projects.
-
E.
Amy E. Duddleston
Amy E. Duddleston is an American film editor known for her work on major studio features and acclaimed television series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec66593c819091ecf0c553e0aead |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.