Triple
T4771249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hertzian waves |
E105930
|
entity |
| Predicate | areExampleOf |
P1259
|
FINISHED |
| Object | radio-frequency radiation |
—
|
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: radio-frequency radiation | Statement: [Hertzian waves, areExampleOf, radio-frequency radiation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areExampleOf Context triple: [Hertzian waves, areExampleOf, radio-frequency radiation]
-
A.
hasExample
chosen
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
C.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
D.
areRepresentedBy
Indicates that one entity serves as a representation, proxy, or stand-in for another entity.
-
E.
areClassifiedBy
Indicates that entities are assigned to one or more categories, types, or classes according to a specified classification scheme.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.