Triple
T9809272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K2 mission |
E238226
|
entity |
| Predicate | numberOfCampaigns |
P90130
|
FINISHED |
| Object | 19 |
—
|
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: 19 | Statement: [K2 mission, numberOfCampaigns, 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCampaigns Context triple: [K2 mission, numberOfCampaigns, 19]
-
A.
numberOfCampaignsApprox
Indicates an approximate count of campaigns associated with or relevant to a given entity.
-
B.
conductedCampaignsIn
Indicates that an entity organized or carried out campaigns within a specified location or region.
-
C.
campaigns
Indicates that an entity actively conducts or participates in an organized effort or series of actions aimed at achieving a specific goal, often in political, marketing, or advocacy contexts.
-
D.
numberOfCallsToAction
Indicates the quantity of distinct calls to action associated with or contained within an item, event, or interaction.
-
E.
supportedCampaignOf
Indicates that one entity actively backed, promoted, or provided assistance to the campaign associated with another entity.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb21ef32c8190ab4b09d157798451 |
completed | April 2, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:29 p.m.