Triple
T13238599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Always (1989 film) |
E315218
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Al Yackey |
E509651
|
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: Al Yackey | Statement: [Always (1989 film), character, Al Yackey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al Yackey Context triple: [Always (1989 film), character, Al Yackey]
-
A.
Al Yackey
chosen
Al Yackey is a character from the comic strip "Always."
-
B.
Alaskey
Alaskey is the surname of Joe Alaskey, an American voice actor best known for portraying iconic Looney Tunes characters such as Bugs Bunny and Daffy Duck.
-
C.
Yarmy
Yarmy is the birth surname of American comedian and actor Don Adams, best known for starring as Maxwell Smart in the television series "Get Smart."
-
D.
Yobo
Yobo is a fictional character from "The Norby Chronicles," a science fiction series by Janet and Isaac Asimov centered on the adventures of a quirky robot and his human companion.
-
E.
Weeley
Weeley is a small village and civil parish in the Tendring district of Essex, England, known for its rural character and proximity to the Essex coast.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff323a3c8190b46b24e69e653105 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:23 p.m.