Triple
T3968464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wedding Crashers |
E92271
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Bob Fisher
Bob Fisher is an American screenwriter best known for co-writing the hit comedy film "Wedding Crashers."
|
E407136
|
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: Bob Fisher | Statement: [Wedding Crashers, writer, Bob Fisher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Fisher Context triple: [Wedding Crashers, writer, Bob Fisher]
-
A.
Ronald Fish
Ronald Fish is a fictional character in P. G. Wodehouse’s Blandings Castle stories, known as one of Lord Emsworth’s amiable but often troublesome younger relatives.
-
B.
Frank Fisk
Frank Fisk is an individual notable enough to be recognized as a bearer of the surname Fisk.
-
C.
Jonathan Fisk
Jonathan Fisk was an early 19th-century American politician who served as a U.S. Representative from New York.
-
D.
Roger Ferris
Roger Ferris is the fictional CIA operative protagonist of the espionage thriller "Body of Lies," known for navigating complex Middle Eastern intelligence operations.
-
E.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
- 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: Bob Fisher Triple: [Wedding Crashers, writer, Bob Fisher]
Generated description
Bob Fisher is an American screenwriter best known for co-writing the hit comedy film "Wedding Crashers."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bob Fisher Target entity description: Bob Fisher is an American screenwriter best known for co-writing the hit comedy film "Wedding Crashers."
-
A.
Ronald Fish
Ronald Fish is a fictional character in P. G. Wodehouse’s Blandings Castle stories, known as one of Lord Emsworth’s amiable but often troublesome younger relatives.
-
B.
Frank Fisk
Frank Fisk is an individual notable enough to be recognized as a bearer of the surname Fisk.
-
C.
Jonathan Fisk
Jonathan Fisk was an early 19th-century American politician who served as a U.S. Representative from New York.
-
D.
Roger Ferris
Roger Ferris is the fictional CIA operative protagonist of the espionage thriller "Body of Lies," known for navigating complex Middle Eastern intelligence operations.
-
E.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef992d6bc8190be1b244eb87f2964 |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c443e208190a8bf83ec642a142e |
completed | March 14, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69b5505592bc8190bedda7df9eef8fa7 |
completed | March 14, 2026, 12:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b550e241048190aaa72504bc278c98 |
completed | March 14, 2026, 12:13 p.m. |
Created at: March 9, 2026, 3:32 p.m.