Triple
T7950752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Holiday |
E184606
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Matthew Kragen
Matthew Kragen is the wealthy, self-serving retail magnate and primary antagonist in the comedy film "Last Holiday."
|
E720067
|
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: Matthew Kragen | Statement: [Last Holiday, character, Matthew Kragen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Kragen Context triple: [Last Holiday, character, Matthew Kragen]
-
A.
Matthew Stuecken
Matthew Stuecken is a film screenwriter best known for co-writing the psychological sci-fi thriller "10 Cloverfield Lane."
-
B.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
C.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
-
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: Matthew Kragen Triple: [Last Holiday, character, Matthew Kragen]
Generated description
Matthew Kragen is the wealthy, self-serving retail magnate and primary antagonist in the comedy film "Last Holiday."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Kragen Target entity description: Matthew Kragen is the wealthy, self-serving retail magnate and primary antagonist in the comedy film "Last Holiday."
-
A.
Matthew Stuecken
Matthew Stuecken is a film screenwriter best known for co-writing the psychological sci-fi thriller "10 Cloverfield Lane."
-
B.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
C.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
-
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_69ca8292cba881908a64427b938dac47 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b5b7450819091e4e6f21e9d832d |
completed | March 31, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd33cf48188190b57ac2fb1dbfa771 |
completed | April 1, 2026, 3:03 p.m. |
| NEDg | Description generation | batch_69cd36ecc1d88190a978f1d51b0e1382 |
completed | April 1, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4e7822e48190bb573162f224bd8c |
completed | April 1, 2026, 4:57 p.m. |
Created at: March 30, 2026, 5:10 p.m.