Triple
T8416684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Minutes Hate |
E198744
|
entity |
| Predicate | reinforcesConcept |
P50891
|
FINISHED |
| Object | cult of Big Brother |
—
|
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: cult of Big Brother | Statement: [Two Minutes Hate, reinforcesConcept, cult of Big Brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reinforcesConcept Context triple: [Two Minutes Hate, reinforcesConcept, cult of Big Brother]
-
A.
reinforcedPrinciple
chosen
Indicates that one entity has strengthened, supported, or validated a principle associated with another entity, making that principle more firmly established or accepted.
-
B.
reinforcedIn
Indicates that one entity is strengthened, supported, or made more robust within, or as a result of conditions in, another entity or context.
-
C.
trainingConcept
Indicates that one entity serves as a concept, topic, or subject matter that is being taught or trained on in relation to another entity.
-
D.
demonstratedConcept
Indicates that an entity has shown, illustrated, or made evident a particular concept through example, explanation, or action.
-
E.
refinedConcept
Indicates that one concept is a more precise, detailed, or specialized version of another concept.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c5121081908efa3eca25406d3a |
completed | March 31, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.