Triple
T3968463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wedding Crashers |
E92271
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Steve Faber
Steve Faber is an American screenwriter best known for co-writing the hit comedy film "Wedding Crashers."
|
E401244
|
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: Steve Faber | Statement: [Wedding Crashers, writer, Steve Faber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Faber Context triple: [Wedding Crashers, writer, Steve Faber]
-
A.
Steve Ferrone
Steve Ferrone is an English drummer best known for his long tenure with Tom Petty and the Heartbreakers as well as his extensive work as a session and touring musician.
-
B.
Greg Finton
Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
-
C.
Brad Dorros
Brad Dorros is a film and television producer known for his work on projects such as the thriller "The Fifth Estate."
-
D.
Marcus T. Paulk
Marcus T. Paulk is an American actor and rapper best known for his role as Myles Mitchell on the television sitcom "Moesha."
-
E.
Fred Tatasciore
Fred Tatasciore is an American voice actor known for his deep, powerful vocal performances in numerous animated series, films, and video games, often portraying larger-than-life or monstrous characters.
- 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: Steve Faber Triple: [Wedding Crashers, writer, Steve Faber]
Generated description
Steve Faber 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: Steve Faber Target entity description: Steve Faber is an American screenwriter best known for co-writing the hit comedy film "Wedding Crashers."
-
A.
Steve Ferrone
Steve Ferrone is an English drummer best known for his long tenure with Tom Petty and the Heartbreakers as well as his extensive work as a session and touring musician.
-
B.
Greg Finton
Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
-
C.
Brad Dorros
Brad Dorros is a film and television producer known for his work on projects such as the thriller "The Fifth Estate."
-
D.
Marcus T. Paulk
Marcus T. Paulk is an American actor and rapper best known for his role as Myles Mitchell on the television sitcom "Moesha."
-
E.
Fred Tatasciore
Fred Tatasciore is an American voice actor known for his deep, powerful vocal performances in numerous animated series, films, and video games, often portraying larger-than-life or monstrous characters.
- 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_69b533c189a88190b3a81c63621b98ac |
completed | March 14, 2026, 10:09 a.m. |
| NEDg | Description generation | batch_69b53470617c8190ab92103943c8ac7b |
completed | March 14, 2026, 10:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5352cae14819097fdf02b324fe814 |
completed | March 14, 2026, 10:15 a.m. |
Created at: March 9, 2026, 3:32 p.m.