Triple
T19164313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado House of Representatives |
E469136
|
entity |
| Predicate | numberOfLegislativeSessionsPerTerm |
P11319
|
FINISHED |
| Object | 1 regular session per year |
—
|
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: 1 regular session per year | Statement: [Colorado House of Representatives, numberOfLegislativeSessionsPerTerm, 1 regular session per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLegislativeSessionsPerTerm Context triple: [Colorado House of Representatives, numberOfLegislativeSessionsPerTerm, 1 regular session per year]
-
A.
hasLegislativeSessionCount
chosen
Indicates the number of legislative sessions associated with a given legislative body, term, or jurisdiction.
-
B.
legislativeTermNumber
Indicates the ordinal number assigned to a specific legislative term within a sequence of legislative periods.
-
C.
numberOfLegislatures
Indicates the total count of distinct legislatures associated with or relevant to a given entity.
-
D.
legislativePeriod
Indicates the specific legislative term or session during which an action, event, or status is valid or took place.
-
E.
legislativePeriodicity
Indicates how frequently a legislative body or process recurs or is scheduled to occur over time.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f15e2720819084b1707497db26a2 |
completed | April 20, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.