Triple
T15752564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wish You Well |
E381881
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Karen Spiegel |
E683357
|
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: Karen Spiegel | Statement: [Wish You Well, producer, Karen Spiegel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Spiegel Context triple: [Wish You Well, producer, Karen Spiegel]
-
A.
Karen S. Spiegel
chosen
Karen S. Spiegel is a film producer best known for her work on the political thriller "Absolute Power."
-
B.
Katherine Spiegel
Katherine Spiegel was the wife of prominent American film director and producer Mervyn LeRoy.
-
C.
Kathy Speer
Kathy Speer is an American television writer and producer best known for her work on popular sitcoms such as The Golden Girls and its spin-off The Golden Palace.
-
D.
Lesley Vogel
Lesley Vogel is an American actress and television producer best known as the mother of actress Hayden Panettiere.
-
E.
Karen Ziemba
Karen Ziemba is a Tony Award–winning American actress, singer, and dancer best known for her work in musical theatre on Broadway.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05030e31081908c307a8dc7067db4 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff998397688190a77b6a7c5b542f7e |
completed | May 9, 2026, 8:30 p.m. |
Created at: April 10, 2026, 4:47 a.m.