Triple
T1637578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulitzer Prize for Editorial Cartooning |
E35390
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object |
Mike Luckovich
Mike Luckovich is an American editorial cartoonist renowned for his sharp political commentary and award-winning work in major newspapers.
|
E189415
|
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: Mike Luckovich | Statement: [Pulitzer Prize for Editorial Cartooning, notableRecipient, Mike Luckovich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Luckovich Context triple: [Pulitzer Prize for Editorial Cartooning, notableRecipient, Mike Luckovich]
-
A.
Matthew Freund
Matthew Freund is a film editor known for his work on the comedy movie "Fist Fight."
-
B.
Matt Weitzman
Matt Weitzman is an American television writer and producer best known as a co-creator and executive producer of the animated series "American Dad!"
-
C.
Chad Mirkin
Chad Mirkin is an American chemist and nanotechnology pioneer known for inventing dip-pen nanolithography and developing spherical nucleic acids for biomedical applications.
-
D.
Joshua Michael Stern
Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
-
E.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
- 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: Mike Luckovich Triple: [Pulitzer Prize for Editorial Cartooning, notableRecipient, Mike Luckovich]
Generated description
Mike Luckovich is an American editorial cartoonist renowned for his sharp political commentary and award-winning work in major newspapers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Luckovich Target entity description: Mike Luckovich is an American editorial cartoonist renowned for his sharp political commentary and award-winning work in major newspapers.
-
A.
Matthew Freund
Matthew Freund is a film editor known for his work on the comedy movie "Fist Fight."
-
B.
Matt Weitzman
Matt Weitzman is an American television writer and producer best known as a co-creator and executive producer of the animated series "American Dad!"
-
C.
Chad Mirkin
Chad Mirkin is an American chemist and nanotechnology pioneer known for inventing dip-pen nanolithography and developing spherical nucleic acids for biomedical applications.
-
D.
Joshua Michael Stern
Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
-
E.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a192d588190bbfa4693ed787c05 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71a61de8819095005c222ec50810 |
completed | March 8, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_69ad728cb27c8190802b30afc5e259e2 |
completed | March 8, 2026, 12:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad72fa21208190b596bfdfc69043bd |
completed | March 8, 2026, 1 p.m. |
Created at: March 4, 2026, 7:28 p.m.