Triple
T15008581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Greenfield |
E377774
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Lilly Greenfield |
E377774
|
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: Lilly Greenfield | Statement: [Max Greenfield, child, Lilly Greenfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilly Greenfield Context triple: [Max Greenfield, child, Lilly Greenfield]
-
A.
Lilly Greenfield
chosen
Lilly Greenfield is the daughter of American actor Max Greenfield.
-
B.
Lilly Wust
Lilly Wust was a German housewife in Nazi-era Berlin whose real-life love affair with the Jewish woman Felice Schragenheim inspired the story depicted in "Aimée & Jaguar."
-
C.
Lottie Kaufman
Lottie Kaufman was the wife of pioneering American film producer and Paramount Pictures founder Adolph Zukor.
-
D.
Lila Leeds
Lila Leeds was an American film actress of the 1940s best known for her roles in crime dramas and for a highly publicized 1948 marijuana arrest that derailed her Hollywood career.
-
E.
Lila Norcross
Lila Norcross is a central protagonist in Stephen King and Owen King’s novel "Sleeping Beauties," serving as a key figure navigating the chaos that erupts when women around the world fall into a mysterious sleep.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5ae816c8190a36abb46bbdaad7b |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:55 a.m.