Triple
T23340420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tormented |
E591719
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Tom Stewart |
—
|
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: Tom Stewart | Statement: [Tormented, hasMainCharacter, Tom Stewart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Stewart Context triple: [Tormented, hasMainCharacter, Tom Stewart]
-
A.
Tom Stewart
chosen
Tom Stewart is an actor known for his role in the film "American Gigolo."
-
B.
Kevin Stevens
Kevin Stevens is a former American NHL power forward best known for his high-scoring seasons with the Pittsburgh Penguins in the early 1990s.
-
C.
Jim Stewart
Jim Stewart is a film editor known for his work on the animated feature "Monsters, Inc."
-
D.
Jim Stewart
Jim Stewart was an American record producer and co-founder of the influential soul music label Stax Records in Memphis, Tennessee.
-
E.
Matt Stewart
Matt Stewart is the widowed father and high school teacher at the center of the sitcom "Raising Dad," struggling to raise his two daughters with the help of his own father.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198329d9c8190992627afa9b54bed |
completed | April 29, 2026, 5:33 a.m. |
Created at: April 17, 2026, 5:18 p.m.