Triple
T17728945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Proffitt |
E442538
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Frank Proffitt |
—
|
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 Proffitt | Statement: [Frank Proffitt, name, Frank Proffitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Proffitt Context triple: [Frank Proffitt, name, Frank Proffitt]
-
A.
Frank Proffitt
chosen
Frank Proffitt was an American Appalachian folk musician and ballad singer known for preserving and popularizing traditional songs such as "Tom Dooley."
-
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.
Joe Noland
Joe Noland is a fictional character from the television series "The District," which follows the professional and personal lives of law enforcement officials in Washington, D.C.
-
D.
John Farris
John Farris is an American novelist and screenwriter best known for his horror and suspense fiction, including the novel that inspired Brian De Palma’s film "The Fury."
-
E.
Jerry Finnerman
Jerry Finnerman was an American cinematographer best known for his visually distinctive work on the original Star Trek 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e4ae5c8190a6f0743f7e74b5bf |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 10:08 a.m.