Triple
T28416702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Hampshire Republican presidential primary, 2024 |
E719826
|
entity |
| Predicate | hasIssueFocus |
P11722
|
FINISHED |
| Object | economic policy debates among Republican candidates |
—
|
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: economic policy debates among Republican candidates | Statement: [New Hampshire Republican presidential primary, 2024, hasIssueFocus, economic policy debates among Republican candidates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIssueFocus Context triple: [New Hampshire Republican presidential primary, 2024, hasIssueFocus, economic policy debates among Republican candidates]
-
A.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
hasTargetIssue
chosen
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
-
C.
containsIssue
Indicates that one entity includes, encompasses, or has within it a particular issue, problem, or defect.
-
D.
hasRecentIssue
Indicates that an entity is associated with an issue or problem that has occurred within a recent or specified time frame.
-
E.
hasFirstIssueContext
Indicates that a subject is associated with the contextual information or circumstances surrounding its first issue or occurrence.
- 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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6645ba71c81908044ade6ab577018 |
completed | May 2, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 1:30 a.m.