Triple
T21638124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Simple Wish |
E534013
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Martin Short |
—
|
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: Martin Short | Statement: [A Simple Wish, starring, Martin Short]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Short Context triple: [A Simple Wish, starring, Martin Short]
-
A.
Martin Short
chosen
Martin Short is a Canadian-American comedian and actor renowned for his energetic characters and work on sketch comedy shows, films, and Broadway.
-
B.
Al Murray
Al Murray is a British comedian and television personality best known for his pub landlord character and sharp, observational stand-up comedy.
-
C.
Kevin Allen
Kevin Allen is a British actor and director known for his work in film and television, including directing the cult comedy "Twin Town."
-
D.
Chris Elliott
Chris Elliott is an American actor and comedian known for his offbeat roles in film and television, including his supporting role in the comedy classic "Groundhog Day."
-
E.
Will Murray
Will Murray is an American writer best known for his extensive work continuing classic pulp fiction series, particularly the Doc Savage novels.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef538eef0481908f5bf0e27f8e054d |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 16, 2026, 6:35 p.m.