Triple
T19416202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ref |
E485722
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Don Simpson |
—
|
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: Don Simpson | Statement: [The Ref, producer, Don Simpson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Simpson Context triple: [The Ref, producer, Don Simpson]
-
A.
Don Simpson
chosen
Don Simpson was a prominent Hollywood film producer known for co-producing blockbuster action films such as "Top Gun," "Beverly Hills Cop," and "Bad Boys."
-
B.
Red Simpson
Red Simpson was an American country singer-songwriter best known for his truck-driving songs and contributions to the Bakersfield sound movement.
-
C.
John Hampson Simpson
John Hampson Simpson was the husband of renowned German actress Therese Giehse.
-
D.
Lyndon Sims
Lyndon Sims is an individual notable primarily for bearing the given name "Lyndon."
-
E.
Scott Simpson
Scott Simpson is an American professional golfer best known for winning the 1987 U.S. Open and having a standout amateur career before turning pro.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af9c8fc81909860de10b6720207 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.