Triple
T31119959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana congressional delegation |
E793194
|
entity |
| Predicate | hasElectionsFrequencyForSenate |
P1678
|
FINISHED |
| Object | every 2 years for one-third of Senate seats |
—
|
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: every 2 years for one-third of Senate seats | Statement: [Louisiana congressional delegation, hasElectionsFrequencyForSenate, every 2 years for one-third of Senate seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectionsFrequencyForSenate Context triple: [Louisiana congressional delegation, hasElectionsFrequencyForSenate, every 2 years for one-third of Senate seats]
-
A.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
B.
legislativePeriodicity
chosen
Indicates how frequently a legislative body or process recurs or is scheduled to occur over time.
-
C.
constitutionalFrequency
Indicates how often a constitutional or fundamental condition, symptom, or state occurs over a given period.
-
D.
numberOfSeatsInSenate
Indicates the total count of seats allocated in a given senate.
-
E.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
- 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 29, 2026, 9:04 p.m.