Triple
T2919293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tootsie |
E78679
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Teri Garr |
E152918
|
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: Teri Garr | Statement: [Tootsie, starring, Teri Garr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teri Garr Context triple: [Tootsie, starring, Teri Garr]
-
A.
Teri Garr
chosen
Teri Garr is an American actress known for her versatile performances in films such as "Young Frankenstein," "Close Encounters of the Third Kind," and "Tootsie."
-
B.
Cindy Williams
Cindy Williams was an American actress best known for her role as Shirley Feeney on the hit television sitcom "Laverne & Shirley."
-
C.
Barbara Bach
Barbara Bach is an American actress and former model best known for playing Bond girl Anya Amasova in the James Bond film "The Spy Who Loved Me."
-
D.
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.
-
E.
Kim Fields
Kim Fields is an American actress best known for her role as Dorothy "Tootie" Ramsey on the sitcom *The Facts of Life* and later as Regine Hunter on *Living Single*.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a53f8c8190b188d549f1161e84 |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1de8b9378819084861d65dd2b9528 |
completed | March 11, 2026, 9:28 p.m. |
Created at: March 8, 2026, 2:54 p.m.