Triple
T8842877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Underground Railroad |
E210430
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Mark Ceryak
Mark Ceryak is a film and television producer best known for his work on the acclaimed series "The Underground Railroad."
|
E761027
|
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: Mark Ceryak | Statement: [The Underground Railroad, executiveProducer, Mark Ceryak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Ceryak Context triple: [The Underground Railroad, executiveProducer, Mark Ceryak]
-
A.
Michael Cerenzie
Michael Cerenzie is a film producer known for his work on independent and genre films in Hollywood.
-
B.
Mark Korven
Mark Korven is a Canadian film and television composer best known for his unsettling, atmospheric scores for horror projects such as The Witch and The Lighthouse.
-
C.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
D.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
E.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
- 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: Mark Ceryak Triple: [The Underground Railroad, executiveProducer, Mark Ceryak]
Generated description
Mark Ceryak is a film and television producer best known for his work on the acclaimed series "The Underground Railroad."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Ceryak Target entity description: Mark Ceryak is a film and television producer best known for his work on the acclaimed series "The Underground Railroad."
-
A.
Michael Cerenzie
Michael Cerenzie is a film producer known for his work on independent and genre films in Hollywood.
-
B.
Mark Korven
Mark Korven is a Canadian film and television composer best known for his unsettling, atmospheric scores for horror projects such as The Witch and The Lighthouse.
-
C.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
D.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
E.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc608946cc8190bed3c340ba303b9c |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89a41a2c8190b69e5a1b157f9325 |
completed | April 3, 2026, 9:34 a.m. |
| NEDg | Description generation | batch_69cf8b6d7a008190ae02f525b903619b |
completed | April 3, 2026, 9:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf8be7fa488190a5eb6d3f26718e46 |
completed | April 3, 2026, 9:44 a.m. |
Created at: March 30, 2026, 6:48 p.m.