Triple
T20241814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class of 1999 |
E498314
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Scott Conrad |
—
|
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: Scott Conrad | Statement: [Class of 1999, editor, Scott Conrad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Conrad Context triple: [Class of 1999, editor, Scott Conrad]
-
A.
Scott Conrad
chosen
Scott Conrad is a film editor best known for his Academy Award-winning work on the boxing drama "Rocky."
-
B.
Tom Huffman
Tom Huffman is a television producer best known for serving as an executive producer on the reality series "Basketball Wives."
-
C.
Ron Estes
Ron Estes is a Republican politician serving as the U.S. Representative for Kansas's 4th congressional district.
-
D.
Mike Donnelly
Mike Donnelly is the well-meaning but accident-prone protagonist of the comedy film "Black Sheep," whose misadventures jeopardize his brother’s political campaign.
-
E.
Mike E. Smith
Mike E. Smith is a Hall of Fame American jockey renowned for winning numerous major races, including multiple Breeders’ Cup events and Triple Crown classics.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716eabf48190ae4e760f472114bd |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.