Triple
T21116811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes Man (film) |
E520319
|
entity |
| Predicate | leadCharacter |
P1668
|
FINISHED |
| Object | Carl Allen |
—
|
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: Carl Allen | Statement: [Yes Man (film), leadCharacter, Carl Allen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carl Allen Context triple: [Yes Man (film), leadCharacter, Carl Allen]
-
A.
Carl Allen
Carl Allen is an American jazz drummer and bandleader known for his dynamic style and extensive work with leading contemporary jazz ensembles.
-
B.
Carl Allen
chosen
Carl Allen is the main protagonist of the comedy film "Yes Man," a man who transforms his life by committing to say "yes" to every opportunity that comes his way.
-
C.
Harry Allen
Harry Allen is the central protagonist of the 2007 romantic drama film "Married Life," around whom the story’s marital tensions and moral dilemmas revolve.
-
D.
Glen Tullman
Glen Tullman is an American healthcare technology entrepreneur and executive best known for leading and building major digital health companies, including Allscripts.
-
E.
Clark Allen
Clark Allen was an American actor known for his guest appearance in classic television, including an episode of The Twilight Zone titled "Five Characters in Search of an Exit."
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72106a3b48190a0efa51a74ae21f0 |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:55 p.m.