Triple
T31785004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 United States Senate elections |
E811303
|
entity |
| Predicate | issueContext |
P29037
|
FINISHED |
| Object | economic recession and high unemployment |
—
|
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 recession and high unemployment | Statement: [2010 United States Senate elections, issueContext, economic recession and high unemployment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: issueContext Context triple: [2010 United States Senate elections, issueContext, economic recession and high unemployment]
-
A.
issue
Indicates that an entity formally publishes, releases, or distributes something, such as a document, statement, or item, often in an official or authoritative capacity.
-
B.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
C.
issuesMark
Indicates that one entity assigns or gives a mark, grade, or score to another entity.
-
D.
issueIncludes
Indicates that an issue or problem encompasses, contains, or involves a specified element, component, or sub-issue as part of its scope.
-
E.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
- 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 30, 2026, 11:37 p.m.