Triple
T19553254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dead and Gone |
E489243
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | James Scheffer |
—
|
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: James Scheffer | Statement: [Dead and Gone, writer, James Scheffer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Scheffer Context triple: [Dead and Gone, writer, James Scheffer]
-
A.
James Scheffer
chosen
James Scheffer, better known as Jim Jonsin, is an American record producer and songwriter recognized for crafting hit tracks across hip hop and pop music.
-
B.
Joseph Weishaar
Joseph Weishaar is an American architect and designer best known for winning the competition to create the National World War I Memorial in Washington, D.C.
-
C.
Alan Schaefer
Alan Schaefer is the main special-forces commando protagonist, nicknamed "Dutch," portrayed by Arnold Schwarzenegger in the 1987 science fiction action film Predator.
-
D.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
E.
Eric Schoffstall
Eric Schoffstall is a software developer best known for creating Gulp, a popular JavaScript-based task runner used in web development build workflows.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d315c68819087402802d624a8c9 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:41 p.m.