Triple
T15724289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perrey Reeves |
E381182
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Aaron Endress-Fox
Aaron Endress-Fox is an American film editor known for his work in television and for being married to actress Perrey Reeves.
|
E1173325
|
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: Aaron Endress-Fox | Statement: [Perrey Reeves, spouse, Aaron Endress-Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aaron Endress-Fox Context triple: [Perrey Reeves, spouse, Aaron Endress-Fox]
-
A.
Jason Fuchs
Jason Fuchs is an American screenwriter and actor best known for writing major studio films such as Wonder Woman (2017) and Pan (2015).
-
B.
Aaron M. Frey
Aaron M. Frey is an American lawyer and Democratic politician who serves as the chief legal officer for the state of Maine.
-
C.
Jesse M. Feldman
Jesse M. Feldman is a cinematographer known for his work on feature films such as the holiday comedy "The Perfect Holiday."
-
D.
Nicholas Nayfack
Nicholas Nayfack was a mid-20th-century American film producer best known for his work on influential science fiction cinema.
-
E.
Andrew Braunsberg
Andrew Braunsberg is a film producer best known for his work on the acclaimed 1979 satirical comedy-drama "Being There."
- 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: Aaron Endress-Fox Triple: [Perrey Reeves, spouse, Aaron Endress-Fox]
Generated description
Aaron Endress-Fox is an American film editor known for his work in television and for being married to actress Perrey Reeves.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aaron Endress-Fox Target entity description: Aaron Endress-Fox is an American film editor known for his work in television and for being married to actress Perrey Reeves.
-
A.
Jason Fuchs
Jason Fuchs is an American screenwriter and actor best known for writing major studio films such as Wonder Woman (2017) and Pan (2015).
-
B.
Aaron M. Frey
Aaron M. Frey is an American lawyer and Democratic politician who serves as the chief legal officer for the state of Maine.
-
C.
Jesse M. Feldman
Jesse M. Feldman is a cinematographer known for his work on feature films such as the holiday comedy "The Perfect Holiday."
-
D.
Nicholas Nayfack
Nicholas Nayfack was a mid-20th-century American film producer best known for his work on influential science fiction cinema.
-
E.
Andrew Braunsberg
Andrew Braunsberg is a film producer best known for his work on the acclaimed 1979 satirical comedy-drama "Being There."
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb1fdd4819088f3e243263e5f73 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f68bf881909e5ad8a6ab81684a |
completed | May 9, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_69ff8388b3588190ae55c123bb19cb2c |
completed | May 9, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff84125e808190a4d465d9effad639 |
completed | May 9, 2026, 6:59 p.m. |
Created at: April 10, 2026, 4:46 a.m.