Triple
T13975513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halt and Catch Fire |
E336177
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jonathan Lisco |
E179118
|
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: Jonathan Lisco | Statement: [Halt and Catch Fire, executiveProducer, Jonathan Lisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Lisco Context triple: [Halt and Catch Fire, executiveProducer, Jonathan Lisco]
-
A.
Jonathan Lisco
chosen
Jonathan Lisco is an American television writer, producer, and showrunner known for his work on series such as Animal Kingdom, Halt and Catch Fire, and Jack & Bobby.
-
B.
Lawrence DiStasi
Lawrence DiStasi is an American theater artist and director best known as a co-founder and longtime ensemble member of Chicago’s Lookingglass Theatre Company.
-
C.
Jeffrey Licon
Jeffrey Licon is an American actor best known for playing Carlos García on the Nickelodeon family sitcom "The Brothers García."
-
D.
Jonathan Sanger
Jonathan Sanger is an American film producer and director best known for his work on acclaimed films such as "The Elephant Man."
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e90dc148190b38e339aac0de484 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e72b9f08190a33e8e20541edd21 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 9, 2026, 10:18 p.m.