Triple
T4706350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kentucky House of Representatives |
E104396
|
entity |
| Predicate | evenYearSessionLength |
P43788
|
FINISHED |
| Object | 60 legislative days |
—
|
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: 60 legislative days | Statement: [Kentucky House of Representatives, evenYearSessionLength, 60 legislative days]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evenYearSessionLength Context triple: [Kentucky House of Representatives, evenYearSessionLength, 60 legislative days]
-
A.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
B.
evennessProperty
chosen
Indicates that a quantity, value, or count has the property of being even, typically divisible into two equal integer parts without remainder.
-
C.
hasAverageYearLength
Indicates that one entity has a specified average duration for its year (orbital period), typically measured over time.
-
D.
meetsBetweenSessionsOf
Indicates that one entity meets another during the interval between scheduled sessions or events.
-
E.
additionalDaysPerYear
Indicates the number of extra days added each year to a base or standard duration.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.