Triple
T827704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vox |
E17891
|
entity |
| Predicate | politicalPositionOnSocialIssues |
P4795
|
FINISHED |
| Object | socially conservative |
—
|
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: socially conservative | Statement: [Vox, politicalPositionOnSocialIssues, socially conservative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalPositionOnSocialIssues Context triple: [Vox, politicalPositionOnSocialIssues, socially conservative]
-
A.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
B.
policyStance
chosen
Indicates the position or viewpoint an entity holds regarding a specific policy or set of policies.
-
C.
socialIssue
Indicates a relationship where something is recognized or treated as a problem or concern affecting society or a community at large.
-
D.
politicalIdentity
Indicates the political affiliation, ideology, or stance that characterizes an entity’s position within a political spectrum or system.
-
E.
politicalTendency
Indicates the general political orientation, leaning, or ideological stance associated with an entity in relation to the political spectrum.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab99b1e48190afad1f073348b29a |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.