Triple
T15441073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Langella |
E369900
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sarah Langella |
E369900
|
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: Sarah Langella | Statement: [Sarah Langella, name, Sarah Langella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Langella Context triple: [Sarah Langella, name, Sarah Langella]
-
A.
Sarah Langella
chosen
Sarah Langella is the daughter of American stage and screen actor Frank Langella.
-
B.
Judith Ivey
Judith Ivey is an American actress and director known for her Tony Award–winning stage performances and numerous roles in film and television.
-
C.
Jane Alexander
Jane Alexander is an acclaimed American actress and former chair of the National Endowment for the Arts, known for her extensive work in film, television, and theater.
-
D.
Rhea Perlman
Rhea Perlman is an American actress best known for her Emmy-winning role as the sharp-tongued waitress Carla Tortelli on the classic sitcom "Cheers."
-
E.
Diane Baker
Diane Baker is an American actress and producer known for her work in film and television since the late 1950s, including roles in classics like "The Diary of Anne Frank" and "Marnie."
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec4e868819092739e71118d43b0 |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 3:21 a.m.