Triple
T5101151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Severance |
E114982
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Dan Erickson |
E494436
|
NE FINISHED |
How this triple was built (2 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: Dan Erickson | Statement: [Severance, executiveProducer, Dan Erickson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Erickson Context triple: [Severance, executiveProducer, Dan Erickson]
-
A.
Dan Erickson
chosen
Dan Erickson is a television writer and producer best known for creating the acclaimed sci-fi thriller series "Severance."
-
B.
Josh Gudwin
Josh Gudwin is a Grammy-winning Canadian recording and mixing engineer best known for his work with major pop artists such as Justin Bieber.
-
C.
Charles Ardai
Charles Ardai is an American writer, editor, and entrepreneur best known as the founder of the Hard Case Crime imprint and for his award-winning crime and mystery fiction.
-
D.
Dan Jewett
Dan Jewett is an American science teacher known for his brief marriage to billionaire philanthropist and novelist MacKenzie Scott.
-
E.
Patrick Nielsen Hayden
Patrick Nielsen Hayden is an influential American science fiction and fantasy editor and publisher, known for shaping the careers of numerous prominent genre authors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7584ed408190a6d1086588f24faa |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becfc467008190ae704139f21edae2 |
completed | March 21, 2026, 5:05 p.m. |
Created at: March 20, 2026, 1:40 p.m.