Triple
T16049999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Adler |
E389327
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Jay Adler |
E504638
|
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: Jay Adler | Statement: [Jacob Adler, child, Jay Adler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Adler Context triple: [Jacob Adler, child, Jay Adler]
-
A.
Jay Adler
chosen
Jay Adler was an American character actor known for his supporting roles in numerous mid-20th-century films and television series.
-
B.
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.
-
C.
Jerry Adler
Jerry Adler is an American actor and theatre director best known for his character roles in film, television, and on Broadway.
-
D.
Jeremy Adelman
Jeremy Adelman is a composer best known for creating music for television, including the series "Hart of Dixie."
-
E.
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.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18361083c8190abc84534265dc992 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb8b1b2c8190949943b20f2f8574 |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:56 a.m.