Triple
T18731353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunshine Cleaning |
E458041
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Megan Holley |
—
|
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 Holley | Statement: [Sunshine Cleaning, screenwriter, Megan Holley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Holley Context triple: [Sunshine Cleaning, screenwriter, Megan Holley]
-
A.
Megan Holley
chosen
Megan Holley is an American screenwriter best known for writing the indie dramedy film "Sunshine Cleaning."
-
B.
Megan McClure
Megan McClure is an American volleyball player best known as a standout outside hitter for Stanford University's powerhouse women's volleyball program.
-
C.
Megan Gill
Megan Gill is a film editor best known for her work on major feature films, including the superhero movie "X-Men Origins: Wolverine."
-
D.
Megan Terry
Megan Terry is an influential American playwright and pioneer of feminist and experimental theatre, best known for works like "Viet Rock."
-
E.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7854748190b66c4aaadfd67f29 |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.