Triple
T11704840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creeping Winter |
E278211
|
entity |
| Predicate | addsCampaignSetting |
P97930
|
FINISHED |
| Object | snow-covered environments |
—
|
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: snow-covered environments | Statement: [Creeping Winter, addsCampaignSetting, snow-covered environments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsCampaignSetting Context triple: [Creeping Winter, addsCampaignSetting, snow-covered environments]
-
A.
campaignSetting
chosen
Indicates the broader narrative world or environment within which a particular campaign, story, or activity takes place.
-
B.
effectOnCampaign
Indicates the influence or impact that one factor has on the outcome or performance of a campaign.
-
C.
campaignConnection
Indicates a relationship where two entities are linked through participation in, association with, or influence within the same campaign or related campaigns.
-
D.
plannedCampaign
Indicates that an entity has designed and scheduled a campaign to be executed in the future.
-
E.
hasCampaignName
Indicates that an entity is associated with a specific campaign identified by a particular name.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49c8c38819083d83f5fdec52b7f |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.