Triple
T18944005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Suburbans |
E463459
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Megan Ward |
—
|
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: Megan Ward | Statement: [The Suburbans, starring, Megan Ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Ward Context triple: [The Suburbans, starring, Megan Ward]
-
A.
Megan Ward
chosen
Megan Ward is an American actress best known for her roles in 1990s films and television series, including the comedy film "Encino Man."
-
B.
Kelly Lynch
Kelly Lynch is an American actress known for her roles in films such as "Drugstore Cowboy," "Road House," and various television series.
-
C.
Kirsten Bales
Kirsten Bales is the wife of American actor Jon Heder, known for his role in the film "Napoleon Dynamite."
-
D.
Marielle Scott
Marielle Scott is an American actress known for her work in film and television, including roles in projects like the miniseries "A Teacher."
-
E.
Megan Ferguson
Megan Ferguson is an American actress known for her work in television comedies and dramas, including a prominent role in the series "The Comedians."
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d53e6e0c81908a547e21c4819bac |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 10, 2026, 11:59 a.m.