Triple
T558301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloisonnism |
E11991
|
entity |
| Predicate | typicalSubjectMatter |
P450
|
FINISHED |
| Object | landscapes |
—
|
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: landscapes | Statement: [Cloisonnism, typicalSubjectMatter, landscapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSubjectMatter Context triple: [Cloisonnism, typicalSubjectMatter, landscapes]
-
A.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
B.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
D.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
E.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.