Triple
T21480776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammy Tell Me True |
E529982
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Sandra Dee |
—
|
NE NERFINISHED |
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: Sandra Dee | Statement: [Tammy Tell Me True, starring, Sandra Dee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandra Dee Context triple: [Tammy Tell Me True, starring, Sandra Dee]
-
A.
Sandra Dee
chosen
Sandra Dee was an American actress and teen idol of the late 1950s and 1960s, best known for films like "Gidget" and "A Summer Place."
-
B.
Diana Lynn
Diana Lynn was an American film and television actress best known for her work in 1940s and 1950s Hollywood comedies and dramas.
-
C.
Pat Farrah
Pat Farrah is an American retail executive best known as a co-founder of The Home Depot and a key architect of the big-box home improvement store concept.
-
D.
Debbie Rowe
Debbie Rowe is an American nurse best known as Michael Jackson’s ex-wife and the mother of two of his children.
-
E.
Lala Kent
Lala Kent is an American reality television personality, actress, and entrepreneur best known for her role on Bravo's "Vanderpump Rules."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1b0130819088b8e96ddbb29317 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:20 p.m.