Triple
T14647958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salon of 1850–1851 |
E343903
|
entity |
| Predicate | subjectMatterTrend |
P39078
|
FINISHED |
| Object | contemporary rural life |
—
|
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: contemporary rural life | Statement: [Salon of 1850–1851, subjectMatterTrend, contemporary rural life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectMatterTrend Context triple: [Salon of 1850–1851, subjectMatterTrend, contemporary rural life]
-
A.
trends
chosen
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
B.
intellectualTrend
Indicates a relationship where an idea, movement, or way of thinking is recognized as an intellectual trend influencing thought or discourse.
-
C.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
D.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
E.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ebe8048190a2935d00c9cfd8be |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.