Triple
T20620989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Day After |
E506695
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | JoBeth Williams |
—
|
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: JoBeth Williams | Statement: [The Day After, castMember, JoBeth Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JoBeth Williams Context triple: [The Day After, castMember, JoBeth Williams]
-
A.
JoBeth Williams
chosen
JoBeth Williams is an American actress known for her roles in films such as "Poltergeist," "The Big Chill," and numerous television movies and series.
-
B.
Cindy Williams
Cindy Williams is a fictional character from the British soap opera "EastEnders," known for her tumultuous relationships and connections to the Beale family.
-
C.
Cindy Williams
Cindy Williams is a screenwriter known for her work on the influential 1977 car-chase film "Grand Theft Auto."
-
D.
Cindy Williams
Cindy Williams was an American actress best known for her role as Shirley Feeney on the hit television sitcom "Laverne & Shirley."
-
E.
June Lockhart
June Lockhart is an American actress best known for her roles in classic television series such as "Lassie" and the original "Lost in Space."
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe19ca481908c896bec49a025cd |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.