Triple
T6887888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonya Wilde |
E158966
|
entity |
| Predicate | hasEthnicTheme |
P27835
|
FINISHED |
| Object | racial identity |
—
|
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: racial identity | Statement: [Sonya Wilde, hasEthnicTheme, racial identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicTheme Context triple: [Sonya Wilde, hasEthnicTheme, racial identity]
-
A.
hasEthnicCharacteristic
chosen
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
B.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character of, another entity.
-
C.
depictsEthnicContext
Indicates that one entity visually represents or portrays the ethnic background, identity, or cultural context associated with another entity.
-
D.
hasEthnolinguisticContext
Indicates that something is associated with, shaped by, or understood within a specific ethnolinguistic (cultural and language-based) context.
-
E.
isUsedByEthnicGroup
Indicates that something (such as an object, practice, or resource) is utilized or employed by a particular ethnic group.
- 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_69c688342f6c8190ad7eea6ba262db99 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d9101e30819084695ba0003a255c |
completed | March 27, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b53e9881909ec298daa9f1913b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:23 p.m.