Triple
T4985345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Norman |
E111986
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ralph Norman |
E111986
|
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: Ralph Norman | Statement: [Ralph Norman, name, Ralph Norman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Norman Context triple: [Ralph Norman, name, Ralph Norman]
-
A.
Ralph Norman
chosen
Ralph Norman is a Republican politician and businessman serving as the U.S. Representative for South Carolina's 5th congressional district.
-
B.
Richard Hudson
Richard Hudson is the child of Katherine Hudson, known primarily in relation to her.
-
C.
Joe Hutshing
Joe Hutshing is an American film editor known for his work on major Hollywood films, including collaborations with directors like Oliver Stone and Cameron Crowe.
-
D.
Chip Roy
Chip Roy is a conservative Republican politician and attorney serving in the U.S. House of Representatives from Texas.
-
E.
Mike Royce
Mike Royce is an American television writer and producer known for his work on acclaimed comedy series such as Everybody Loves Raymond and the 2017 reboot of One Day at a Time.
- 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_69bd441be7bc8190b530362d427b97d2 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd725766d88190b6fda860a005ce4e |
completed | March 20, 2026, 4:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a1ca3ec81908ad750cd9e899bcc |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:33 p.m.