Triple
T10776572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love and Death |
E254211
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Ronald Kalish
Ronald Kalish is an editor known for his work on the film "Love and Death."
|
E1006543
|
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: Ronald Kalish | Statement: [Love and Death, editedBy, Ronald Kalish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronald Kalish Context triple: [Love and Death, editedBy, Ronald Kalish]
-
A.
John Altschuler
John Altschuler is an American television writer and producer best known for co-creating and producing the animated series "King of the Hill" and "Silicon Valley."
-
B.
Leo Salkin
Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
-
C.
Philip Mandelker
Philip Mandelker is a film and television producer best known for his work as an executive producer on projects such as "Something About Amelia."
-
D.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
-
E.
Guy Rothblum
Guy Rothblum is a theoretical computer scientist known for his work in cryptography and complexity theory.
- 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: Ronald Kalish Triple: [Love and Death, editedBy, Ronald Kalish]
Generated description
Ronald Kalish is an editor known for his work on the film "Love and Death."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ronald Kalish Target entity description: Ronald Kalish is an editor known for his work on the film "Love and Death."
-
A.
John Altschuler
John Altschuler is an American television writer and producer best known for co-creating and producing the animated series "King of the Hill" and "Silicon Valley."
-
B.
Leo Salkin
Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
-
C.
Philip Mandelker
Philip Mandelker is a film and television producer best known for his work as an executive producer on projects such as "Something About Amelia."
-
D.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
-
E.
Guy Rothblum
Guy Rothblum is a theoretical computer scientist known for his work in cryptography and complexity theory.
- F. None of above. chosen
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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7329d8c908190bddad40685133ea1 |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b76e0cc8190aa7303347e0183d4 |
completed | May 3, 2026, 12:48 a.m. |
| NEDg | Description generation | batch_69f69d48e6948190a13afe3b8943d877 |
completed | May 3, 2026, 12:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69dfa2b8481908827025a28bfb056 |
completed | May 3, 2026, 12:59 a.m. |
Created at: April 8, 2026, 9:16 p.m.