Triple
T3858716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grown Ups |
E90082
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Keith Schwab
Keith Schwab is a film editor known for his work on the comedy movie "Grown Ups."
|
E392927
|
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: Keith Schwab | Statement: [Grown Ups, editedBy, Keith Schwab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keith Schwab Context triple: [Grown Ups, editedBy, Keith Schwab]
-
A.
Brian Schmetzer
Brian Schmetzer is an American soccer coach best known for leading Seattle Sounders FC to multiple MLS Cup titles and establishing the club as a perennial league contender.
-
B.
Eric D. Schneider
Eric D. Schneider was a scientist and author known for his work on thermodynamics and complex systems, particularly in collaboration with Dorion Sagan.
-
C.
David Schmaier
David Schmaier is a technology executive and entrepreneur best known as a co-founder of Siebel Systems, a pioneering customer relationship management (CRM) software company.
-
D.
Scott Kroopf
Scott Kroopf is an American film producer known for his work on numerous Hollywood features, including the science-fiction adventure film "Zathura: A Space Adventure."
-
E.
Michael T. Sauer
Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
- 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: Keith Schwab Triple: [Grown Ups, editedBy, Keith Schwab]
Generated description
Keith Schwab is a film editor known for his work on the comedy movie "Grown Ups."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Keith Schwab Target entity description: Keith Schwab is a film editor known for his work on the comedy movie "Grown Ups."
-
A.
Brian Schmetzer
Brian Schmetzer is an American soccer coach best known for leading Seattle Sounders FC to multiple MLS Cup titles and establishing the club as a perennial league contender.
-
B.
Eric D. Schneider
Eric D. Schneider was a scientist and author known for his work on thermodynamics and complex systems, particularly in collaboration with Dorion Sagan.
-
C.
David Schmaier
David Schmaier is a technology executive and entrepreneur best known as a co-founder of Siebel Systems, a pioneering customer relationship management (CRM) software company.
-
D.
Scott Kroopf
Scott Kroopf is an American film producer known for his work on numerous Hollywood features, including the science-fiction adventure film "Zathura: A Space Adventure."
-
E.
Michael T. Sauer
Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1e68f88190941c39221486f6ae |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b504228220819082e11b316ba79b08 |
completed | March 14, 2026, 6:45 a.m. |
| NEDg | Description generation | batch_69b505420de0819086dee340f34a8886 |
completed | March 14, 2026, 6:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5064192a48190a0f95dee872437e0 |
completed | March 14, 2026, 6:54 a.m. |
Created at: March 9, 2026, 3:19 p.m.