Triple
T19886797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzie Toller |
E477919
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Sam Lombardo |
—
|
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: Sam Lombardo | Statement: [Suzie Toller, associatedWithCharacter, Sam Lombardo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Lombardo Context triple: [Suzie Toller, associatedWithCharacter, Sam Lombardo]
-
A.
Sam Lombardo
chosen
Sam Lombardo is the charismatic high school guidance counselor at the center of the twisting sexual assault and conspiracy plot in the 1998 neo-noir thriller film "Wild Things."
-
B.
Lou Lombardo
Lou Lombardo was a film editor known for his work on notable movies including the romantic comedy-drama "Moonstruck."
-
C.
Tony Lombardo
Tony Lombardo is a film editor known for his work on the comedy movie "Van Wilder."
-
D.
Joe Viterelli
Joe Viterelli was an American character actor best known for his comedic portrayals of tough, mob-connected figures in films such as "Analyze This" and its sequel.
-
E.
Joseph Lombardo
Joseph Lombardo was a notorious Chicago mobster and reputed capo in the Chicago Outfit, known for his involvement in organized crime and high-profile federal prosecutions.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65909fe0481908e22b60d04fe2b11 |
completed | April 20, 2026, 4:49 p.m. |
Created at: April 10, 2026, 1:52 p.m.