Triple
T27425596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado Revised Statutes Title 39 |
E690474
|
entity |
| Predicate | containsRulesFor |
P6249
|
FINISHED |
| Object | tax return filing in Colorado |
—
|
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: tax return filing in Colorado | Statement: [Colorado Revised Statutes Title 39, containsRulesFor, tax return filing in Colorado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRulesFor Context triple: [Colorado Revised Statutes Title 39, containsRulesFor, tax return filing in Colorado]
-
A.
hasRuleFor
Indicates that one entity defines or applies a rule that governs or constrains another entity or situation.
-
B.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
C.
hasRuleOver
Indicates that one entity holds authority, control, or governance over another entity.
-
D.
usesRulesFrom
chosen
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another entity.
-
E.
hasNumberOfRules
Indicates the specific count of rules associated with or applicable to an entity.
- 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 27, 2026, 12:40 p.m.