Triple
T10256898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Zakheim |
E240493
|
entity |
| Predicate | hasNotableSubjectOfStudy |
P494
|
FINISHED |
| Object | Bernard Zakheim murals |
—
|
LITERAL 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: Bernard Zakheim murals | Statement: [Nathan Zakheim, hasNotableSubjectOfStudy, Bernard Zakheim murals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSubjectOfStudy Context triple: [Nathan Zakheim, hasNotableSubjectOfStudy, Bernard Zakheim murals]
-
A.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
B.
isSubjectOfStudy
Indicates that an entity is the focus or topic being examined, researched, or analyzed in a study or investigation.
-
C.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
-
D.
hasNotableScholar
Indicates that an entity is associated with a scholar who is recognized as particularly distinguished or influential in relation to that entity.
-
E.
hasNotableSubject
chosen
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
- F. None of above.
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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:31 a.m.