Triple
T14657092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Shift |
E344138
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Shelley Long |
E326155
|
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: Shelley Long | Statement: [Night Shift, portrayedBy, Shelley Long]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shelley Long Context triple: [Night Shift, portrayedBy, Shelley Long]
-
A.
Shelley Long
chosen
Shelley Long is an American actress best known for her Emmy-winning role as Diane Chambers on the television sitcom "Cheers."
-
B.
Lisa Crouse
Lisa Crouse is a relative of Nico Blue Hoon, the daughter of late Blind Melon frontman Shannon Hoon.
-
C.
Mary Lynn Rajskub
Mary Lynn Rajskub is an American actress and comedian best known for her role as Chloe O'Brian on the television series "24."
-
D.
Courteney Cox
Courteney Cox is an American actress best known for playing Monica Geller on the hit television sitcom "Friends."
-
E.
Kirstie Alley
Kirstie Alley was an American actress best known for her Emmy-winning role as Rebecca Howe on the hit sitcom "Cheers" and for her work in films like "Look Who's Talking."
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51a562c819098971447db4b29f7 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe729f894881908647da558bef1031 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 10, 2026, 1:27 a.m.