Triple
T3933341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Daley |
E90847
|
entity |
| Predicate | familyMember |
P566
|
FINISHED |
| Object |
Nick Daley
Nick Daley is a fictional character from the "Night at the Museum" film series, known as the son of protagonist Larry Daley.
|
E435579
|
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: Nick Daley | Statement: [Larry Daley, familyMember, Nick Daley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Daley Context triple: [Larry Daley, familyMember, Nick Daley]
-
A.
Darren Morfitt
Darren Morfitt is a British actor known for his roles in television dramas and genre series, including appearances in Doctor Who.
-
B.
Dan Janvey
Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
-
C.
Chris Larkin
Chris Larkin is a British actor known for his work in film, television, and theatre, and for being the son of acclaimed actress Maggie Smith.
-
D.
Jon Plowman
Jon Plowman is a British television producer best known for his influential work on BBC comedies, including series such as Absolutely Fabulous and The Office.
-
E.
Derek Dowding
Derek Dowding was a Royal Air Force officer and the son of Air Chief Marshal Hugh Dowding, noted for his own distinguished service in military aviation.
- 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: Nick Daley Triple: [Larry Daley, familyMember, Nick Daley]
Generated description
Nick Daley is a fictional character from the "Night at the Museum" film series, known as the son of protagonist Larry Daley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nick Daley Target entity description: Nick Daley is a fictional character from the "Night at the Museum" film series, known as the son of protagonist Larry Daley.
-
A.
Darren Morfitt
Darren Morfitt is a British actor known for his roles in television dramas and genre series, including appearances in Doctor Who.
-
B.
Dan Janvey
Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
-
C.
Chris Larkin
Chris Larkin is a British actor known for his work in film, television, and theatre, and for being the son of acclaimed actress Maggie Smith.
-
D.
Jon Plowman
Jon Plowman is a British television producer best known for his influential work on BBC comedies, including series such as Absolutely Fabulous and The Office.
-
E.
Derek Dowding
Derek Dowding was a Royal Air Force officer and the son of Air Chief Marshal Hugh Dowding, noted for his own distinguished service in military aviation.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcab1808190bf653f29062cdddb |
completed | March 9, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e4ca9164819088b261d148e0d379 |
completed | March 14, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69b5e5d675808190a5a9767f253f0178 |
completed | March 14, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5e66837e081908ac5a0079485cd18 |
completed | March 14, 2026, 10:51 p.m. |
Created at: March 9, 2026, 3:23 p.m.