Triple
T12597895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawn King |
E300779
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Shawn Southwick |
E90767
|
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: Shawn Southwick | Statement: [Shawn King, alsoKnownAs, Shawn Southwick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shawn Southwick Context triple: [Shawn King, alsoKnownAs, Shawn Southwick]
-
A.
Shawn Southwick
chosen
Shawn Southwick is an American singer, actress, and television host best known for her long-term marriage to broadcaster Larry King.
-
B.
Matthew F. Leonetti
Matthew F. Leonetti is an American cinematographer known for his work on numerous Hollywood films across action, comedy, and science fiction genres.
-
C.
Steve Ridgeway
Steve Ridgeway is a television producer best known for his role as an executive producer on the late-night talk program "The Jay Leno Show."
-
D.
Christopher Cibelli
Christopher Cibelli is a film editor known for his work on the basketball drama movie "Above the Rim."
-
E.
Brian Reilly
Brian Reilly is a film producer best known for his work on the popular Christmas comedy movie "The Santa Clause."
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d096d08190afa1f685bad68d35 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8c0510081909459662cb91a82b4 |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 9, 2026, 5:08 p.m.