Triple
T159780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lerner family |
E3256
|
entity |
| Predicate | ethnicBackground |
P194
|
FINISHED |
| Object | Jewish-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: Jewish-American | Statement: [Lerner family, ethnicBackground, Jewish-American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicBackground Context triple: [Lerner family, ethnicBackground, Jewish-American]
-
A.
ethnicOrigin
chosen
Indicates the relationship where an entity is associated with a particular ethnic group or ancestry.
-
B.
relatedEthnicGroup
Indicates that there is a notable ethnic connection or association between two ethnic groups, such as shared ancestry, culture, or historical ties.
-
C.
recognizedAsMinorityIn
Indicates that an entity is officially acknowledged or classified as belonging to a minority group within a specified context or jurisdiction.
-
D.
ethnonym
Indicates that one entity is the name of an ethnic group used to refer to the people associated with another entity.
-
E.
hasSignificantPopulationGroup
Indicates that an entity contains or is associated with a notable or substantial subgroup of a population, distinguished by shared characteristics or attributes.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25855baf48190a1b63f2e5865d957 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25660c2a48190b4174d5e6da3cb9d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.