Triple
T28910496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temperature Rising |
E733207
|
entity |
| Predicate | hasArtistEthnicOrCulturalBackground |
P136184
|
FINISHED |
| Object | Afro-European |
—
|
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: Afro-European | Statement: [Temperature Rising, hasArtistEthnicOrCulturalBackground, Afro-European]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtistEthnicOrCulturalBackground Context triple: [Temperature Rising, hasArtistEthnicOrCulturalBackground, Afro-European]
-
A.
artistEthnicity
chosen
Indicates that an artist has a specific ethnic background or affiliation.
-
B.
hasEthnicOrRegionalOrigin
Indicates that an entity originates from, or is associated with, a particular ethnic group or geographic region.
-
C.
hasAuthorCulturalIdentity
Indicates that an author is associated with a particular cultural identity or background.
-
D.
hasEthnicScope
Indicates that something is relevant or applicable specifically to a particular ethnic group or ethnic context.
-
E.
hasCulturalRoots
Indicates that something originates from, is shaped by, or is deeply connected to particular cultural traditions, practices, or heritage.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 28, 2026, 8:11 a.m.