Triple
T4795669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Loving |
E106704
|
entity |
| Predicate | spouseEthnicity |
P59312
|
FINISHED |
| Object | African American and Native American (Mildred Loving) |
—
|
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: African American and Native American (Mildred Loving) | Statement: [Richard Loving, spouseEthnicity, African American and Native American (Mildred Loving)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseEthnicity Context triple: [Richard Loving, spouseEthnicity, African American and Native American (Mildred Loving)]
-
A.
spouseCountryOfCitizenship
Indicates the country in which a person's spouse holds legal citizenship.
-
B.
spouseGender
Indicates the gender of a person’s spouse in a marital relationship.
-
C.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
- F. None of above. chosen
Provenance (4 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6b40c29c8190adab3503f8ba0145 |
completed | March 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69bd622f88188190a51d52ccfad3d2dd |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6b3fb598819084a83d2b765a62b0 |
completed | March 20, 2026, 3:43 p.m. |
Created at: March 20, 2026, 1:22 p.m.