Triple
T11392981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SELRES |
E269891
|
entity |
| Predicate | typicalTrainingFrequency |
P16914
|
FINISHED |
| Object | one weekend a month |
—
|
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: one weekend a month | Statement: [SELRES, typicalTrainingFrequency, one weekend a month]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrainingFrequency Context triple: [SELRES, typicalTrainingFrequency, one weekend a month]
-
A.
typicalTraining
Indicates that an entity commonly undergoes or is associated with a standard or usual form of training in relation to another entity or context.
-
B.
typicalUpdateFrequency
Indicates how often an entity is usually updated or refreshed over time.
-
C.
typicalPeriod
Indicates the usual or characteristic time interval or duration associated with an event, process, or state.
-
D.
performedFrequency
chosen
Indicates how often an action or activity is carried out within a given time period.
-
E.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001796f48190822526f52e3f0337 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.