Triple
T11298617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vic Bubas |
E267516
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Art Heyman |
E711257
|
NE FINISHED |
How this triple was built (2 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: Art Heyman | Statement: [Vic Bubas, notableStudent, Art Heyman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Art Heyman Context triple: [Vic Bubas, notableStudent, Art Heyman]
-
A.
Art Heyman
chosen
Art Heyman was an American basketball player best known as a star at Duke University and a key figure in the early years of the American Basketball Association.
-
B.
Mark Herron
Mark Herron was an American actor best known for being the fourth husband of legendary entertainer Judy Garland.
-
C.
Andy Hamill
Andy Hamill is an individual notable primarily for sharing the surname "Hamill" with others of that name, though specific widely recognized biographical or professional details about him are not well established.
-
D.
Guy Heeley
Guy Heeley is a British film producer known for his work on a range of feature films, including the 2019 thriller "Serenity."
-
E.
Douglas Heyes
Douglas Heyes was an American television and film writer, director, and producer known for his work on classic series such as The Twilight Zone and numerous TV movies and miniseries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a3616c8190a8fd23ca67463806 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a3e26e88190991127a5993a32a4 |
completed | April 19, 2026, 5 p.m. |
Created at: April 8, 2026, 9:32 p.m.