Triple
T21638676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hostages |
E534029
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jonathan Littman |
—
|
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: Jonathan Littman | Statement: [Hostages, executiveProducer, Jonathan Littman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Littman Context triple: [Hostages, executiveProducer, Jonathan Littman]
-
A.
Jonathan Littman
chosen
Jonathan Littman is a television producer best known for his executive production work on the CSI franchise and other major crime and drama series.
-
B.
Michael Pemulis
Michael Pemulis is a brilliant but self-destructive teenage tennis player and drug dealer in David Foster Wallace’s novel "Infinite Jest," known for his cunning, technical genius, and elaborate pranks.
-
C.
Matthew Salsberg
Matthew Salsberg is a television writer and producer best known for his work on the dark comedy series "Weeds."
-
D.
Josh Kesselman
Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
-
E.
Adam Siegel
Adam Siegel is a film producer known for working on major Hollywood action and crime movies, including the 2013 film "2 Guns."
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef538fb12481908f70ad8dbe1d99e4 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 16, 2026, 6:35 p.m.