Triple
T2978108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formula One |
E80445
|
entity |
| Predicate | regulationChangeFrequency |
P26668
|
FINISHED |
| Object | regularly updated technical and sporting rules |
—
|
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: regularly updated technical and sporting rules | Statement: [Formula One, regulationChangeFrequency, regularly updated technical and sporting rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulationChangeFrequency Context triple: [Formula One, regulationChangeFrequency, regularly updated technical and sporting rules]
-
A.
changesEvery
Indicates that one entity undergoes a change whenever or each time another specified condition, event, or entity changes.
-
B.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
-
C.
isFrequently
chosen
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
-
D.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
E.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad999b0d50819093dac7678b887a9b |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.