Triple
T9741498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wedding Ringer |
E236195
|
entity |
| Predicate | cinematography |
P1953
|
FINISHED |
| Object |
Brad Lipson
Brad Lipson is a cinematographer known for his work on feature films such as the comedy "The Wedding Ringer."
|
E818834
|
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: Brad Lipson | Statement: [The Wedding Ringer, cinematography, Brad Lipson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brad Lipson Context triple: [The Wedding Ringer, cinematography, Brad Lipson]
-
A.
Tim Lippe
Tim Lippe is the naive, small-town insurance salesman who serves as the protagonist of the comedy film "Cedar Rapids."
-
B.
Stephen Lipson
Stephen Lipson is a British record producer, guitarist, and songwriter known for his work with artists such as Grace Jones, Annie Lennox, and Frankie Goes to Hollywood.
-
C.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
-
D.
Michael Leibert
Michael Leibert was an American theater director and producer best known for establishing the influential Berkeley Repertory Theatre in California.
-
E.
Eric Ladin
Eric Ladin is an American actor known for his roles in television series such as "Generation Kill," "The Killing," and "Boardwalk Empire."
- 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: Brad Lipson Triple: [The Wedding Ringer, cinematography, Brad Lipson]
Generated description
Brad Lipson is a cinematographer known for his work on feature films such as the comedy "The Wedding Ringer."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brad Lipson Target entity description: Brad Lipson is a cinematographer known for his work on feature films such as the comedy "The Wedding Ringer."
-
A.
Tim Lippe
Tim Lippe is the naive, small-town insurance salesman who serves as the protagonist of the comedy film "Cedar Rapids."
-
B.
Stephen Lipson
Stephen Lipson is a British record producer, guitarist, and songwriter known for his work with artists such as Grace Jones, Annie Lennox, and Frankie Goes to Hollywood.
-
C.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
-
D.
Michael Leibert
Michael Leibert was an American theater director and producer best known for establishing the influential Berkeley Repertory Theatre in California.
-
E.
Eric Ladin
Eric Ladin is an American actor known for his roles in television series such as "Generation Kill," "The Killing," and "Boardwalk Empire."
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2af3e48190b83a442cd0e84062 |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1aff2339c8190b164b13b54a40cec |
completed | April 5, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69d1b08ba1f48190830852f9d60e3368 |
completed | April 5, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b124659481909e7a2ecaf01d8a50 |
completed | April 5, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:23 p.m.