Triple
T26928113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Hemings |
E678136
|
entity |
| Predicate | mixedAncestry |
P161332
|
FINISHED |
| Object | African and European descent |
—
|
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 and European descent | Statement: [Harriet Hemings, mixedAncestry, African and European descent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mixedAncestry Context triple: [Harriet Hemings, mixedAncestry, African and European descent]
-
A.
hasEthnicallyMixedPopulation
Indicates that a population is composed of people from multiple distinct ethnic groups rather than being ethnically homogeneous.
-
B.
includesMixedSexRace
Indicates that the group or context involves individuals of more than one sex and more than one race.
-
C.
mixedAt
Indicates that one entity has been combined or blended together with another entity (or entities), typically to form a mixture at a specific time or place.
-
D.
hadNationalityMix
Indicates that an entity possessed a combination of multiple nationalities or national backgrounds.
-
E.
mixedDiscipline
Indicates that an entity involves or combines multiple distinct disciplines, fields, or areas of expertise within a single context or activity.
- 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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62012cba4819091bdeb0dab253365 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
| PDg | Predicate description generation | batch_69f6125e54e0819088ee33a20efcc9e6 |
completed | May 2, 2026, 3:03 p.m. |
Created at: April 27, 2026, 6:10 a.m.