Triple
T6296735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Lynn Rajskub |
E141147
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Matthew Rolph
Matthew Rolph is an American actor and comedian best known for his marriage to actress and comedian Mary Lynn Rajskub.
|
E607555
|
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: Matthew Rolph | Statement: [Mary Lynn Rajskub, spouse, Matthew Rolph]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Rolph Context triple: [Mary Lynn Rajskub, spouse, Matthew Rolph]
-
A.
Matthew Rundell
Matthew Rundell is a film editor known for his work on the action drama movie "Mercury Plains."
-
B.
Andrew Rennison
Andrew Rennison is a British public official known for serving as the inaugural Surveillance Camera Commissioner, overseeing the regulation and ethical use of CCTV and related surveillance technologies in the UK.
-
C.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
D.
Greg Mathieson
Greg Mathieson is an American keyboardist, composer, and producer known for his work in jazz, fusion, and pop music, collaborating with numerous prominent artists.
-
E.
Ian Crafford
Ian Crafford is a film editor best known for his work on the James Bond movie "Never Say Never Again."
- 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: Matthew Rolph Triple: [Mary Lynn Rajskub, spouse, Matthew Rolph]
Generated description
Matthew Rolph is an American actor and comedian best known for his marriage to actress and comedian Mary Lynn Rajskub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Rolph Target entity description: Matthew Rolph is an American actor and comedian best known for his marriage to actress and comedian Mary Lynn Rajskub.
-
A.
Matthew Rundell
Matthew Rundell is a film editor known for his work on the action drama movie "Mercury Plains."
-
B.
Andrew Rennison
Andrew Rennison is a British public official known for serving as the inaugural Surveillance Camera Commissioner, overseeing the regulation and ethical use of CCTV and related surveillance technologies in the UK.
-
C.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
D.
Greg Mathieson
Greg Mathieson is an American keyboardist, composer, and producer known for his work in jazz, fusion, and pop music, collaborating with numerous prominent artists.
-
E.
Ian Crafford
Ian Crafford is a film editor best known for his work on the James Bond movie "Never Say Never Again."
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0643ac2b48190b2db036ce709e7ea |
completed | March 22, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e406787881908648872228d6eac9 |
completed | March 27, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69c6e61218c4819084c170611077f0e6 |
completed | March 27, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e7cc21548190b302e2e31f9cadd0 |
completed | March 27, 2026, 8:25 p.m. |
Created at: March 22, 2026, 4:27 p.m.