Triple
T34990415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | life of Calvin Coolidge |
E1009362
|
entity |
| Predicate | highlightsPolicyArea |
P83753
|
FINISHED |
| Object | tax reduction |
—
|
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: tax reduction | Statement: [life of Calvin Coolidge, highlightsPolicyArea, tax reduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highlightsPolicyArea Context triple: [life of Calvin Coolidge, highlightsPolicyArea, tax reduction]
-
A.
emphasizesPolicyArea
chosen
Indicates that one entity gives particular importance or priority to a specific policy area in its actions, statements, or focus.
-
B.
commonPolicyArea
Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
-
C.
highlights
Indicates that one entity draws special attention to, emphasizes, or visually marks another entity as important or noteworthy.
-
D.
strengthenedPolicyArea
Indicates that an action or event has made a particular policy area more robust, effective, or stringent.
-
E.
coversPolicyArea
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
- 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_69f76dca50dc8190b71f39defe186be8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.