Triple
T15320376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel Colegate |
E366270
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Michael Briggs
Michael Briggs was the husband of British novelist Isabel Colegate, known primarily in relation to her life and work.
|
E1151306
|
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 Briggs | Statement: [Isabel Colegate, spouse, Michael Briggs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Briggs Context triple: [Isabel Colegate, spouse, Michael Briggs]
-
A.
Michael Wise
Michael Wise was a 17th-century English composer and organist known for his church music and service in prominent royal and cathedral posts.
-
B.
Tony Noble
Tony Noble is a British production designer best known for his work on the acclaimed science fiction film "Moon."
-
C.
Joseph Silk
Joseph Silk is a prominent British astrophysicist and cosmologist known for his influential work on the early universe, cosmic microwave background radiation, and galaxy formation.
-
D.
David Briggs
David Briggs was a renowned record producer best known for his extensive work with Neil Young, shaping the sound of several of Young’s most acclaimed albums.
-
E.
George Keister
George Keister was an American architect best known for designing prominent early 20th-century theaters and commercial buildings in New York City.
- 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 Briggs Triple: [Isabel Colegate, spouse, Michael Briggs]
Generated description
Michael Briggs was the husband of British novelist Isabel Colegate, known primarily in relation to her life and work.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Briggs Target entity description: Michael Briggs was the husband of British novelist Isabel Colegate, known primarily in relation to her life and work.
-
A.
Michael Wise
Michael Wise was a 17th-century English composer and organist known for his church music and service in prominent royal and cathedral posts.
-
B.
Tony Noble
Tony Noble is a British production designer best known for his work on the acclaimed science fiction film "Moon."
-
C.
Joseph Silk
Joseph Silk is a prominent British astrophysicist and cosmologist known for his influential work on the early universe, cosmic microwave background radiation, and galaxy formation.
-
D.
David Briggs
David Briggs was a renowned record producer best known for his extensive work with Neil Young, shaping the sound of several of Young’s most acclaimed albums.
-
E.
George Keister
George Keister was an American architect best known for designing prominent early 20th-century theaters and commercial buildings in New York City.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd460288190b5c41f0a0aeee949 |
completed | April 16, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01e9d14c8190bb095d6d5c8ffd6e |
completed | May 9, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_69ff02a62dcc819087eddd2f0b4c29cb |
completed | May 9, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff036153588190ae46fcde257eb3cb |
completed | May 9, 2026, 9:50 a.m. |
Created at: April 10, 2026, 3:16 a.m.