Triple
T16161720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The King of Queens |
E392194
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
David Litt
David Litt is an American television writer and producer best known for his work on the sitcom "The King of Queens."
|
E1203426
|
NE FINISHED |
How this triple was built (4 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: David Litt | Statement: [The King of Queens, executiveProducer, David Litt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Litt Context triple: [The King of Queens, executiveProducer, David Litt]
-
A.
David Litt
David Litt is an American television writer and producer best known for his work on popular sitcoms, including creating and shaping the long-running series "The King of Queens."
-
B.
Douglas Fackler
Douglas Fackler is a bumbling, mild-mannered police cadet character from the "Police Academy" comedy film series.
-
C.
Michael Glouberman
Michael Glouberman is a television writer and producer best known for his work on the acclaimed sitcom "Malcolm in the Middle."
-
D.
Jonathan Littman
Jonathan Littman is a television producer best known for his executive production work on the CSI franchise and other major crime and drama series.
-
E.
Mark Saul
Mark Saul is an American actor and musician best known for his work on television, including sketch comedy and drama series roles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: David Litt Triple: [The King of Queens, executiveProducer, David Litt]
Generated description
David Litt is an American television writer and producer best known for his work on the sitcom "The King of Queens."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Litt Target entity description: David Litt is an American television writer and producer best known for his work on the sitcom "The King of Queens."
-
A.
David Litt
chosen
David Litt is an American television writer and producer best known for his work on popular sitcoms, including creating and shaping the long-running series "The King of Queens."
-
B.
Douglas Fackler
Douglas Fackler is a bumbling, mild-mannered police cadet character from the "Police Academy" comedy film series.
-
C.
Michael Glouberman
Michael Glouberman is a television writer and producer best known for his work on the acclaimed sitcom "Malcolm in the Middle."
-
D.
Jonathan Littman
Jonathan Littman is a television producer best known for his executive production work on the CSI franchise and other major crime and drama series.
-
E.
Mark Saul
Mark Saul is an American actor and musician best known for his work on television, including sketch comedy and drama series roles.
- F. None of above.
Provenance (5 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5ffba88190b9dc7bb9afb6fdf2 |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f83f6ac8190b9f18fe701a9b3ce |
completed | May 10, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a00203a93c4819080e5e1c5b345ba77 |
completed | May 10, 2026, 6:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0020bcdb388190be736469d1b78af8 |
completed | May 10, 2026, 6:07 a.m. |
Created at: April 10, 2026, 5:02 a.m.