Triple
T676388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Rockefeller |
E13085
|
entity |
| Predicate | inferredEthnicity |
P194
|
FINISHED |
| Object | White American |
—
|
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 American | Statement: [William Rockefeller, inferredEthnicity, White American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inferredEthnicity Context triple: [William Rockefeller, inferredEthnicity, White American]
-
A.
ethnicOrigin
chosen
Indicates the relationship where an entity is associated with a particular ethnic group or ancestry.
-
B.
ethnicCategoryIn
Indicates that an entity belongs to or is classified within a specified ethnic category in a given context.
-
C.
affectedEthnicGroup
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
-
D.
involvedEthnicGroup
Indicates that a particular ethnic group participates in, is affected by, or is otherwise associated with the referenced event, situation, or entity.
-
E.
relatedEthnicGroup
Indicates that there is a notable ethnic connection or association between two ethnic groups, such as shared ancestry, culture, or historical ties.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04b2ae881908a5c23453bef8572 |
completed | March 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69a49d1bbd0c81909cfbec30bd17bde7 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.