Triple
T8280246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1980 United States Senate election in Idaho |
E193651
|
entity |
| Predicate | campaignDescriptor |
P82481
|
FINISHED |
| Object | closely watched race |
—
|
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: closely watched race | Statement: [1980 United States Senate election in Idaho, campaignDescriptor, closely watched race]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campaignDescriptor Context triple: [1980 United States Senate election in Idaho, campaignDescriptor, closely watched race]
-
A.
campaignType
Indicates the specific category or kind of campaign an entity is associated with or participates in.
-
B.
promotionalCampaign
Indicates a relationship where one entity organizes or runs a coordinated set of marketing activities aimed at promoting another entity, product, or service.
-
C.
campaignOrService
Indicates that one entity is a campaign and the other is a service that the campaign promotes, uses, or is associated with.
-
D.
campaignSpecific
Indicates that something is restricted or tailored to a particular campaign, rather than being general or shared across multiple campaigns.
-
E.
campaignTheme
Indicates the central idea or message that characterizes and unifies a particular campaign.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ee66e48190af7058b14f3daac9 |
completed | March 31, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:51 p.m.