Triple
T15173860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dobkin |
E362555
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Martin Dobkin
Martin Dobkin is a notable individual recognized for his public and professional contributions, particularly in Canadian municipal politics and community leadership.
|
E1162677
|
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: Martin Dobkin | Statement: [Dobkin, hasNotableBearer, Martin Dobkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Dobkin Context triple: [Dobkin, hasNotableBearer, Martin Dobkin]
-
A.
Cliff Dorfman
Cliff Dorfman is an American screenwriter and filmmaker best known for co-writing the acclaimed sports drama film "Warrior" (2011).
-
B.
Alan Siegel
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
-
C.
Dennis Marks
Dennis Marks is a name shared by several notable individuals, including an American television producer and writer and a British opera director and translator.
-
D.
Don Blum
Don Blum is an American rock drummer best known for his work with the Detroit garage rock band The Von Bondies.
-
E.
Marty Dorfman
Marty Dorfman is a character in Woody Allen's 2016 romantic comedy film "Café Society," set in 1930s Hollywood and New York.
- 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: Martin Dobkin Triple: [Dobkin, hasNotableBearer, Martin Dobkin]
Generated description
Martin Dobkin is a notable individual recognized for his public and professional contributions, particularly in Canadian municipal politics and community leadership.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin Dobkin Target entity description: Martin Dobkin is a notable individual recognized for his public and professional contributions, particularly in Canadian municipal politics and community leadership.
-
A.
Cliff Dorfman
Cliff Dorfman is an American screenwriter and filmmaker best known for co-writing the acclaimed sports drama film "Warrior" (2011).
-
B.
Alan Siegel
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
-
C.
Dennis Marks
Dennis Marks is a name shared by several notable individuals, including an American television producer and writer and a British opera director and translator.
-
D.
Don Blum
Don Blum is an American rock drummer best known for his work with the Detroit garage rock band The Von Bondies.
-
E.
Marty Dorfman
Marty Dorfman is a character in Woody Allen's 2016 romantic comedy film "Café Society," set in 1930s Hollywood and New York.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006501b488190a2ab09dbf1532571 |
completed | April 15, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d3b3fc0819094daf892200bd1ac |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff40fa8b8c8190b75987e897a20cf5 |
completed | May 9, 2026, 2:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff4158866c819087240d56e613f75c |
completed | May 9, 2026, 2:14 p.m. |
Created at: April 10, 2026, 3:09 a.m.