Triple
T13042729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoyt |
E327235
|
entity |
| Predicate | hasNotableSurnameBearer |
P30307
|
FINISHED |
| Object |
Michael Hoyt
Michael Hoyt is an individual notable enough to be recognized as a prominent bearer of the Hoyt surname.
|
E1088146
|
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 Hoyt | Statement: [Hoyt, hasNotableSurnameBearer, Michael Hoyt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Hoyt Context triple: [Hoyt, hasNotableSurnameBearer, Michael Hoyt]
-
A.
Philip M. Breen
Philip M. Breen is a film producer best known for his work on the acclaimed baseball drama "The Natural."
-
B.
Philip Bruns
Philip Bruns was an American character actor best known for his television and film roles in the 1970s and 1980s, including his work on the satirical soap opera "Mary Hartman, Mary Hartman."
-
C.
Richard C. Meyer
Richard C. Meyer was a film editor known for his work on mid-20th-century American movies, including Westerns and genre films.
-
D.
Michael Bostick
Michael Bostick is a film producer known for his work on major Hollywood comedies and family films, including the hit movie "Bruce Almighty."
-
E.
Alan E. Nourse
Alan E. Nourse was an American science fiction author and physician known for works that often explored medical and social themes, including the novel "The Bladerunner."
- 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 Hoyt Triple: [Hoyt, hasNotableSurnameBearer, Michael Hoyt]
Generated description
Michael Hoyt is an individual notable enough to be recognized as a prominent bearer of the Hoyt surname.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Hoyt Target entity description: Michael Hoyt is an individual notable enough to be recognized as a prominent bearer of the Hoyt surname.
-
A.
Philip M. Breen
Philip M. Breen is a film producer best known for his work on the acclaimed baseball drama "The Natural."
-
B.
Philip Bruns
Philip Bruns was an American character actor best known for his television and film roles in the 1970s and 1980s, including his work on the satirical soap opera "Mary Hartman, Mary Hartman."
-
C.
Richard C. Meyer
Richard C. Meyer was a film editor known for his work on mid-20th-century American movies, including Westerns and genre films.
-
D.
Michael Bostick
Michael Bostick is a film producer known for his work on major Hollywood comedies and family films, including the hit movie "Bruce Almighty."
-
E.
Alan E. Nourse
Alan E. Nourse was an American science fiction author and physician known for works that often explored medical and social themes, including the novel "The Bladerunner."
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804f0318819081516e2ca1de6797 |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27f0e59c8190b40213e999c75feb |
completed | May 8, 2026, 12:01 a.m. |
| NEDg | Description generation | batch_69fd2b2363f881909e04edd850166dd5 |
completed | May 8, 2026, 12:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2cf1a1248190a97644dadf1717bc |
completed | May 8, 2026, 12:23 a.m. |
Created at: April 9, 2026, 8:56 p.m.