Triple
T7532099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grease |
E178047
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Didi Conn |
E644469
|
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: Didi Conn | Statement: [Grease, castMember, Didi Conn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Didi Conn Context triple: [Grease, castMember, Didi Conn]
-
A.
Didi Conn
chosen
Didi Conn is an American actress best known for her role as the bubbly, high-voiced Frenchy in the classic film musical "Grease."
-
B.
Nina Pedrad
Nina Pedrad is a television writer and producer known for her work on series such as the mystery-comedy show "Poker Face."
-
C.
Georgia Engel
Georgia Engel was an American actress best known for her soft-spoken, sweetly quirky roles in television comedies such as "The Mary Tyler Moore Show" and "Everybody Loves Raymond."
-
D.
Alicia Witt
Alicia Witt is an American actress, singer-songwriter, and pianist known for her roles in film and television, including appearances in projects like "Mr. Holland's Opus," "Dune," and "The Walking Dead."
-
E.
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.
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f84753fc81908bee2013004ef5fb |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84640cd2c819094d8f72d82c71e67 |
completed | March 28, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:47 p.m.