Triple
T29336571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parliament must meet at least twice a year with not more than six months between sessions |
E743925
|
entity |
| Predicate | minimumNumberOfSessionsPerYear |
P68034
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Parliament must meet at least twice a year with not more than six months between sessions, minimumNumberOfSessionsPerYear, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumNumberOfSessionsPerYear Context triple: [Parliament must meet at least twice a year with not more than six months between sessions, minimumNumberOfSessionsPerYear, 2]
-
A.
minimumSessionsPerYear
chosen
Indicates the smallest number of sessions that must occur within a one-year period.
-
B.
maximumAnnualAppointments
Indicates the highest number of appointments that may be scheduled for an entity within a single year.
-
C.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
-
D.
maximumDaysOfUsePerSeason
Indicates the greatest number of days an entity is allowed or expected to be used within a single season.
-
E.
examSessionFrequency
Indicates how often an exam session occurs within a given period or schedule.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 1:31 p.m.