Triple
T9969860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life in Pieces |
E196176
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Justin Adler |
E831767
|
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: Justin Adler | Statement: [Life in Pieces, executiveProducer, Justin Adler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Justin Adler Context triple: [Life in Pieces, executiveProducer, Justin Adler]
-
A.
Justin Adler
chosen
Justin Adler is an American television writer and producer best known for creating the CBS family sitcom "Life in Pieces."
-
B.
Jon Adler
Jon Adler is a scientific researcher who co-authored a 2021 study published in the journal Nature.
-
C.
Jake Adler
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."
-
D.
Jay Adler
Jay Adler was an American character actor known for his supporting roles in numerous mid-20th-century films and television series.
-
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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b7ea9881908a56f11e2e446dd0 |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257c002cc8190becc9730b2c01782 |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:48 p.m.