Triple
T6361195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Conversation |
E143111
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Cindy Williams |
E103739
|
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: Cindy Williams | Statement: [The Conversation, starring, Cindy Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindy Williams Context triple: [The Conversation, starring, Cindy Williams]
-
A.
Cindy Williams
chosen
Cindy Williams was an American actress best known for her role as Shirley Feeney on the hit television sitcom "Laverne & Shirley."
-
B.
JoBeth Williams
JoBeth Williams is an American actress known for her roles in films such as "Poltergeist," "The Big Chill," and numerous television movies and series.
-
C.
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."
-
D.
Lindsay Crouse
Lindsay Crouse is an American actress known for her work in film, television, and theater, including an Academy Award–nominated role in "Places in the Heart."
-
E.
Jill Eikenberry
Jill Eikenberry is an American actress best known for her Emmy-nominated role as attorney Ann Kelsey on the television series "L.A. Law."
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067fa0d0c819098d01545849142fc |
completed | March 22, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c67c3f115481909879d637fc231556 |
completed | March 27, 2026, 12:46 p.m. |
Created at: March 22, 2026, 4:32 p.m.