Triple
T11971443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Embeth Davidtz |
E284927
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Jason Sloane
Jason Sloane is an American entertainment lawyer known for representing high-profile Hollywood clients and being married to actress Embeth Davidtz.
|
E960103
|
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: Jason Sloane | Statement: [Embeth Davidtz, spouse, Jason Sloane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Sloane Context triple: [Embeth Davidtz, spouse, Jason Sloane]
-
A.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
-
B.
Sam Healy
Sam Healy is a fictional prison counselor and correctional officer in the television series "Orange Is the New Black."
-
C.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
D.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
-
E.
Seth Lochhead
Seth Lochhead is a Canadian screenwriter best known for co-writing the action thriller film "Hanna" (2011).
- 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: Jason Sloane Triple: [Embeth Davidtz, spouse, Jason Sloane]
Generated description
Jason Sloane is an American entertainment lawyer known for representing high-profile Hollywood clients and being married to actress Embeth Davidtz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jason Sloane Target entity description: Jason Sloane is an American entertainment lawyer known for representing high-profile Hollywood clients and being married to actress Embeth Davidtz.
-
A.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
-
B.
Sam Healy
Sam Healy is a fictional prison counselor and correctional officer in the television series "Orange Is the New Black."
-
C.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
D.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
-
E.
Seth Lochhead
Seth Lochhead is a Canadian screenwriter best known for co-writing the action thriller film "Hanna" (2011).
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037d32e88190b1509285dc907d29 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48a9628cc819095d15fd90023e57d |
completed | May 1, 2026, 11:12 a.m. |
| NEDg | Description generation | batch_69f48fc3baac8190af87b55164f00b26 |
completed | May 1, 2026, 11:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f495ab52788190a886f7014267f8e2 |
completed | May 1, 2026, 11:59 a.m. |
Created at: April 8, 2026, 9:46 p.m.