Triple
T21990594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Adler |
E543074
|
entity |
| Predicate | loveInterest |
P7325
|
FINISHED |
| Object | Jake Adler |
—
|
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: Jake Adler | Statement: [Jane Adler, loveInterest, Jake Adler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Adler Context triple: [Jane Adler, loveInterest, Jake Adler]
-
A.
Jake Adler
chosen
Jake Adler is a middle-aged bakery owner and divorced father who becomes entangled in a romantic triangle with his ex-wife and her new love interest in the film "It's Complicated."
-
B.
Jay Adler
Jay Adler was an American character actor known for his supporting roles in numerous mid-20th-century films and television series.
-
C.
Matt Adler
Matt Adler is an American actor and voice actor known for his roles in 1980s films like "Teen Wolf" and "North Shore" as well as various voice performances in later projects.
-
D.
Jake Adelstein
Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
-
E.
Jeremy Adelman
Jeremy Adelman is a composer best known for creating music for television, including the series "Hart of Dixie."
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.