Triple
T26953948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WASP |
E678847
|
entity |
| Predicate | hasEthnoReligiousComponent |
P70164
|
FINISHED |
| Object | white |
—
|
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: white | Statement: [WASP, hasEthnoReligiousComponent, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnoReligiousComponent Context triple: [WASP, hasEthnoReligiousComponent, white]
-
A.
hasEthnoReligiousDimension
chosen
Indicates that the relationship, event, or phenomenon involves or is characterized by an ethnic and/or religious aspect or component.
-
B.
hasEthnoreligiousRole
Indicates that an entity holds a role, function, or status defined by a combined ethnic and religious identity within a given context.
-
C.
hasEthnicOrNationalComposition
Indicates that an entity is characterized by a particular ethnic or national group composition.
-
D.
hasReligiousComposition
Indicates that an entity is characterized by or associated with a particular religious makeup, affiliation, or set of religious components.
-
E.
ethnoreligiousIdentity
Indicates a relationship where an entity is characterized by a combined ethnic and religious group identity.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 6:26 a.m.