Triple
T1809683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luca |
E40302
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Jason Hudak
Jason Hudak is a film and video editor known for his post-production work, including collaborations with filmmaker Luca.
|
E202440
|
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: Jason Hudak | Statement: [Luca, editor, Jason Hudak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Hudak Context triple: [Luca, editor, Jason Hudak]
-
A.
Jonathan Teplitzky
Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
-
B.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
C.
Chris Malachowsky
Chris Malachowsky is an American engineer and entrepreneur best known as a co-founder of NVIDIA, a leading technology company in graphics processing and AI computing.
-
D.
Max Hodak
Max Hodak is an American entrepreneur and technologist best known as the co-founder and former president of Neuralink, a company developing brain–computer interface technology.
-
E.
Jonathan Lisco
Jonathan Lisco is an American television writer, producer, and showrunner known for his work on series such as Animal Kingdom, Halt and Catch Fire, and Jack & Bobby.
- 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: Jason Hudak Triple: [Luca, editor, Jason Hudak]
Generated description
Jason Hudak is a film and video editor known for his post-production work, including collaborations with filmmaker Luca.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jason Hudak Target entity description: Jason Hudak is a film and video editor known for his post-production work, including collaborations with filmmaker Luca.
-
A.
Jonathan Teplitzky
Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
-
B.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
C.
Chris Malachowsky
Chris Malachowsky is an American engineer and entrepreneur best known as a co-founder of NVIDIA, a leading technology company in graphics processing and AI computing.
-
D.
Max Hodak
Max Hodak is an American entrepreneur and technologist best known as the co-founder and former president of Neuralink, a company developing brain–computer interface technology.
-
E.
Jonathan Lisco
Jonathan Lisco is an American television writer, producer, and showrunner known for his work on series such as Animal Kingdom, Halt and Catch Fire, and Jack & Bobby.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c310d88190bfd9c27fa238e648 |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5e352d88190839cde25e3c07d95 |
completed | March 8, 2026, 5:46 p.m. |
| NEDg | Description generation | batch_69adb8b6d160819096dc02323049101d |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb9bafd688190a66a835c6a8163e3 |
completed | March 8, 2026, 6:02 p.m. |
Created at: March 4, 2026, 7:32 p.m.