Triple
T6814317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brothers & Sisters |
E156713
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Michael Morris
Michael Morris is a television director and producer best known for his work on the family drama series "Brothers & Sisters."
|
E621425
|
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: Michael Morris | Statement: [Brothers & Sisters, executiveProducer, Michael Morris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Morris Context triple: [Brothers & Sisters, executiveProducer, Michael Morris]
-
A.
Michael Morris
Michael Morris is a person known primarily as a relative of American professional soccer player Jordan Morris.
-
B.
Michael Sturgis
Michael Sturgis is a member of the musical group Asia.
-
C.
Ken Morris
Ken Morris is a technology entrepreneur best known as a founder of the enterprise software company PeopleSoft.
-
D.
Val Curtis
Val Curtis was a British public health researcher and hygiene expert renowned for her work on sanitation, behavior change, and disease prevention in low- and middle-income countries.
-
E.
Richard Franklin
Richard Franklin was a British actor best known for playing Captain Mike Yates in the classic science fiction television series Doctor Who.
- 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: Michael Morris Triple: [Brothers & Sisters, executiveProducer, Michael Morris]
Generated description
Michael Morris is a television director and producer best known for his work on the family drama series "Brothers & Sisters."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Morris Target entity description: Michael Morris is a television director and producer best known for his work on the family drama series "Brothers & Sisters."
-
A.
Michael Morris
Michael Morris is a person known primarily as a relative of American professional soccer player Jordan Morris.
-
B.
Michael Sturgis
Michael Sturgis is a member of the musical group Asia.
-
C.
Ken Morris
Ken Morris is a technology entrepreneur best known as a founder of the enterprise software company PeopleSoft.
-
D.
Val Curtis
Val Curtis was a British public health researcher and hygiene expert renowned for her work on sanitation, behavior change, and disease prevention in low- and middle-income countries.
-
E.
Richard Franklin
Richard Franklin was a British actor best known for playing Captain Mike Yates in the classic science fiction television series Doctor Who.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d32c40508190932718a649fc1417 |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723dd82048190969754b388a76913 |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c724d740588190a4ed1aa532ee7335 |
completed | March 28, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c725aedfd0819097ae603cc49ff9a8 |
completed | March 28, 2026, 12:49 a.m. |
Created at: March 27, 2026, 2:17 p.m.