Triple
T40982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greta Thunberg |
E807
|
entity |
| Predicate | translatedSlogan |
P1683
|
FINISHED |
| Object | "School strike for climate" |
—
|
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: "School strike for climate" | Statement: [Greta Thunberg, translatedSlogan, "School strike for climate"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: translatedSlogan Context triple: [Greta Thunberg, translatedSlogan, "School strike for climate"]
-
A.
translationOfMotto
chosen
Indicates that one motto is a translation of another motto in a different language.
-
B.
motto
Indicates that one entity serves as the guiding phrase, slogan, or maxim associated with another entity.
-
C.
mottoType
Indicates the specific category or kind of motto that characterizes the relationship between an entity and its motto.
-
D.
nativeLabel
Indicates the label or name of an entity expressed in its own native or original language.
-
E.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24db9527c8190816b6b25c88cb2f4 |
completed | Feb. 28, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69a24ab8a8908190beec6da6694dd4c9 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.