Triple
T14455292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waiting for Guffman |
E358442
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Sheila Albertson |
E270783
|
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: Sheila Albertson | Statement: [Waiting for Guffman, character, Sheila Albertson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheila Albertson Context triple: [Waiting for Guffman, character, Sheila Albertson]
-
A.
Gloria Emerson
Gloria Emerson was an American journalist and author renowned for her searing coverage of the Vietnam War and its human consequences.
-
B.
Sharon Reed
Sharon Reed is a visual effects industry professional best known as one of the founders of the renowned VFX and creative studio Framestore.
-
C.
Barbara Hershey
Barbara Hershey is an American actress known for her intense, emotionally complex performances in film and television, including a prominent role in the psychological thriller "Black Swan."
-
D.
Nancy Richardson
Nancy Richardson is a film editor best known for her work on movies such as the biographical sports comedy-drama "Fighting with My Family."
-
E.
Dina Merrill
chosen
Dina Merrill was an American actress, heiress, and philanthropist known for her elegant screen presence in mid-20th-century Hollywood films and television.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91a8bf088190abf5fd4f646b8c62 |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9280ed081908030a4bbea80398c |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 1:19 a.m.