Triple
T1461173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 United States presidential election |
E31513
|
entity |
| Predicate | campaignFeature |
P19394
|
FINISHED |
| Object | extensive use of social media |
—
|
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: extensive use of social media | Statement: [2016 United States presidential election, campaignFeature, extensive use of social media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campaignFeature Context triple: [2016 United States presidential election, campaignFeature, extensive use of social media]
-
A.
campaignOrService
Indicates that one entity is a campaign and the other is a service that the campaign promotes, uses, or is associated with.
-
B.
campaignType
Indicates the specific category or kind of campaign an entity is associated with or participates in.
-
C.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
D.
campaignTheme
Indicates the central idea or message that characterizes and unifies a particular campaign.
-
E.
specialFeature
chosen
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59ecb60819082217b034e18381f |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.