Triple
T29274924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Jewish politics |
E742221
|
entity |
| Predicate | hasPrimaryGeographicScope |
P199907
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [American Jewish politics, hasPrimaryGeographicScope, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryGeographicScope Context triple: [American Jewish politics, hasPrimaryGeographicScope, United States]
-
A.
hasGeographicSpecificity
Indicates that something is associated with or constrained to a particular geographic location or area.
-
B.
geographicCoverageType
Indicates the type or nature of the geographic area that something covers or applies to.
-
C.
geographicScopeDiscussed
Indicates that the discussion or content addresses, covers, or pertains to a particular geographic area or region.
-
D.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
E.
isGeographicallySpecific
Indicates that something is limited to or uniquely associated with a particular geographic location or area.
- 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_69f0912124d48190a046642b69407f4c |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
| PDg | Predicate description generation | batch_69ff63e5c35081908f69ac44e12b8f52 |
completed | May 9, 2026, 4:42 p.m. |
Created at: April 28, 2026, 12:50 p.m.