Triple
T20416772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detection Club |
E500732
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Len Tyler
Len Tyler is a crime and mystery writer known for his membership in the Detection Club, a prestigious society of detective fiction authors.
|
E1428902
|
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: Len Tyler | Statement: [Detection Club, hasMember, Len Tyler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Len Tyler Context triple: [Detection Club, hasMember, Len Tyler]
-
A.
David Arkin
David Arkin was an American character actor known for his supporting roles in several 1970s films, particularly those directed by Robert Altman.
-
B.
Robert John Reed
Robert John Reed is a British judge who serves as the President of the Supreme Court of the United Kingdom.
-
C.
Jack Byrnes
Jack Byrnes is the overprotective ex-CIA father-in-law character played by Robert De Niro in the comedy film "Meet the Parents."
-
D.
Ian Caldwell
Ian Caldwell is an American novelist best known for co-authoring the bestselling historical thriller "The Rule of Four."
-
E.
James Dadford
James Dadford was a British civil engineer active in the late 18th and early 19th centuries, known for his work on canal construction during the early Industrial Revolution.
- 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: Len Tyler Triple: [Detection Club, hasMember, Len Tyler]
Generated description
Len Tyler is a crime and mystery writer known for his membership in the Detection Club, a prestigious society of detective fiction authors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Len Tyler Target entity description: Len Tyler is a crime and mystery writer known for his membership in the Detection Club, a prestigious society of detective fiction authors.
-
A.
David Arkin
David Arkin was an American character actor known for his supporting roles in several 1970s films, particularly those directed by Robert Altman.
-
B.
Robert John Reed
Robert John Reed is a British judge who serves as the President of the Supreme Court of the United Kingdom.
-
C.
Jack Byrnes
Jack Byrnes is the overprotective ex-CIA father-in-law character played by Robert De Niro in the comedy film "Meet the Parents."
-
D.
Ian Caldwell
Ian Caldwell is an American novelist best known for co-authoring the bestselling historical thriller "The Rule of Four."
-
E.
James Dadford
James Dadford was a British civil engineer active in the late 18th and early 19th centuries, known for his work on canal construction during the early Industrial Revolution.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a4437448190b07b6e6e3de5830f |
completed | April 20, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a087b284bb8819090f76ec27116c619 |
completed | May 16, 2026, 2:11 p.m. |
| NEDg | Description generation | batch_6a088017be588190ab94b8180e44ebf4 |
completed | May 16, 2026, 2:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0880c45e1081908f439ade0c31a47e |
completed | May 16, 2026, 2:35 p.m. |
Created at: April 16, 2026, 11:30 a.m.