Triple
T3798615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 50 First Dates |
E91633
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Adam Sandler |
E16119
|
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: Adam Sandler | Statement: [50 First Dates, starring, Adam Sandler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Sandler Context triple: [50 First Dates, starring, Adam Sandler]
-
A.
Adam Sandler
chosen
Adam Sandler is an American comedian, actor, writer, and producer known for his work on "Saturday Night Live" and a long career of popular comedy films.
-
B.
David Spade
David Spade is an American comedian and actor known for his work on "Saturday Night Live" and in numerous comedy films and television shows.
-
C.
Chris Kattan
Chris Kattan is an American comedian and actor best known for his work on "Saturday Night Live" and roles in films like "A Night at the Roxbury."
-
D.
Ben Stiller
Ben Stiller is an American actor, comedian, and filmmaker known for his leading roles in popular comedy films such as "Zoolander," "Meet the Parents," and "There's Something About Mary."
-
E.
Chris Tucker
Chris Tucker is an American actor and comedian best known for his high-energy performances in the Rush Hour film series and other popular comedies.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7a270908190ac30537a22f3d500 |
completed | March 9, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f061a9e481908d16ae0aa44e2f16 |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:15 p.m.