Triple
T26352526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mérode Altarpiece |
E662939
|
entity |
| Predicate | rightPanelSubject |
P161700
|
FINISHED |
| Object | Saint Joseph |
—
|
NE NERFINISHED |
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: Saint Joseph | Statement: [Mérode Altarpiece, rightPanelSubject, Saint Joseph]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rightPanelSubject Context triple: [Mérode Altarpiece, rightPanelSubject, Saint Joseph]
-
A.
leftPanelSubject
Indicates that an entity serves as the primary subject or focus displayed in the left panel of a user interface or layout.
-
B.
concernsRight
Indicates that something is about or relates specifically to a legal or moral right held by an entity.
-
C.
subjectMVP
Indicates that the subject is considered the most valuable player (MVP) in a given context or event.
-
D.
titleSubjectOf
Indicates that a title (such as a book, article, or work) is about or primarily concerns a particular subject.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- F. None of above. chosen
Provenance (4 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_69ee8130fc44819094e5ab1da201cd7b |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6200ac60481909895c61d050b1338 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 26, 2026, 10:46 p.m.