Triple
T28906150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVN Hall of Fame |
E733083
|
entity |
| Predicate | typicalInductionFrequency |
P203182
|
FINISHED |
| Object | annual |
—
|
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: annual | Statement: [AVN Hall of Fame, typicalInductionFrequency, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalInductionFrequency Context triple: [AVN Hall of Fame, typicalInductionFrequency, annual]
-
A.
typicalFrequencyUnit
Indicates the unit of measurement typically used to express the frequency of an event, action, or occurrence.
-
B.
typicalFSBFrequency
Indicates the usual or characteristic frequency at which a front-side bus (FSB) operates in a given context.
-
C.
typicalInductionSystem
Indicates that one entity is a standard or representative example of an induction system associated with another entity.
-
D.
inductionType
Indicates the specific method or process by which something is brought into a state, condition, or role (e.g., how an entity is initiated, introduced, or caused to occur).
-
E.
inductionSystem
Indicates a relationship where an entity functions as or is associated with an induction-based system (e.g., using electromagnetic induction for operation or control).
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a0136e4af808190b529d324bbf0c5d9 |
completed | May 11, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_6a01369141c4819091cb8064913a44ca |
completed | May 11, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_6a0136e3d6ec8190898b5ab5a628a99d |
completed | May 11, 2026, 1:54 a.m. |
Created at: April 28, 2026, 8:07 a.m.