Triple
T19443953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cromwell |
E486423
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Frank Cordell |
—
|
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: Frank Cordell | Statement: [Cromwell, musicBy, Frank Cordell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Cordell Context triple: [Cromwell, musicBy, Frank Cordell]
-
A.
Frank Cordell
chosen
Frank Cordell was a British composer and conductor best known for his film scores and orchestral arrangements in the mid-20th century.
-
B.
Ray Colcord
Ray Colcord was an American record producer and composer best known for his work in rock music and for scoring numerous television shows.
-
C.
Raymond Cordy
Raymond Cordy was a French character actor known for his prolific work in early 20th-century cinema, particularly in comedies and popular genre films.
-
D.
Charles Dougherty
Charles Dougherty was a prominent 19th-century Georgia jurist and political figure for whom Dougherty County was named.
-
E.
James Congdon
James Congdon is an American actor best known for his character roles in mid-20th-century films and television, including appearances in Westerns and science fiction works.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63387e2048190bfb13fea434ddb46 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.