Triple
T22637936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clerks II |
E558732
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ben Affleck |
—
|
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: Ben Affleck | Statement: [Clerks II, starring, Ben Affleck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ben Affleck Context triple: [Clerks II, starring, Ben Affleck]
-
A.
Ben Affleck
chosen
Ben Affleck is an American actor, director, and screenwriter known for films such as "Good Will Hunting," "Argo," and for portraying Batman in the DC Extended Universe.
-
B.
Ian Affleck
Ian Affleck is a Canadian theoretical physicist known for influential contributions to condensed matter physics and quantum field theory.
-
C.
Matt Damon
Matt Damon is an American actor, producer, and screenwriter known for his versatile performances in films such as Good Will Hunting, the Bourne series, and The Martian.
-
D.
Affleck
Affleck is a surname most prominently associated with American actor and filmmaker Ben Affleck and his brother, actor Casey Affleck.
-
E.
Atticus Affleck
Atticus Affleck is the son of actors Casey Affleck and Summer Phoenix.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1700edb608190ad786ff7fafea0da |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.