Triple
T17331969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Death Wish |
E420837
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Hal Landers
Hal Landers was a film producer best known for his work on the influential 1974 vigilante thriller "Death Wish."
|
E1262830
|
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: Hal Landers | Statement: [Death Wish, producer, Hal Landers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hal Landers Context triple: [Death Wish, producer, Hal Landers]
-
A.
Lew Landers
Lew Landers was a prolific American film and television director best known for his work on low-budget B-movies from the 1930s through the 1960s.
-
B.
Bob Landers
Bob Landers is a fictional character from the American television sitcom "The Debbie Reynolds Show."
-
C.
Ed Leland
Ed Leland is a fictional American intelligence officer and love interest who works undercover in Nazi Germany in the World War II espionage drama film "Shining Through" (1992).
-
D.
David Leland
David Leland is a British screenwriter and director known for his gritty social dramas and collaborations with filmmaker Alan Clarke.
-
E.
Hal Cumpston
Hal Cumpston is an Australian actor best known for his role in the television series "The Walking Dead: World Beyond."
- 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: Hal Landers Triple: [Death Wish, producer, Hal Landers]
Generated description
Hal Landers was a film producer best known for his work on the influential 1974 vigilante thriller "Death Wish."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hal Landers Target entity description: Hal Landers was a film producer best known for his work on the influential 1974 vigilante thriller "Death Wish."
-
A.
Lew Landers
Lew Landers was a prolific American film and television director best known for his work on low-budget B-movies from the 1930s through the 1960s.
-
B.
Bob Landers
Bob Landers is a fictional character from the American television sitcom "The Debbie Reynolds Show."
-
C.
Ed Leland
Ed Leland is a fictional American intelligence officer and love interest who works undercover in Nazi Germany in the World War II espionage drama film "Shining Through" (1992).
-
D.
David Leland
David Leland is a British screenwriter and director known for his gritty social dramas and collaborations with filmmaker Alan Clarke.
-
E.
Hal Cumpston
Hal Cumpston is an Australian actor best known for his role in the television series "The Walking Dead: World Beyond."
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d6870c8190989897aa6beba8ff |
completed | April 19, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c5025d08190ab2581a3b04ae661 |
completed | May 11, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a018e85c91081909a6944ff136e8f50 |
completed | May 11, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a018f7ebf548190b407ebeacbd4d327 |
completed | May 11, 2026, 8:12 a.m. |
Created at: April 10, 2026, 5:43 a.m.