Triple
T30118579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilpin County, Colorado |
E765493
|
entity |
| Predicate | hasLegal |
P94537
|
FINISHED |
| Object | limited-stakes casino gambling |
—
|
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: limited-stakes casino gambling | Statement: [Gilpin County, Colorado, hasLegal, limited-stakes casino gambling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegal Context triple: [Gilpin County, Colorado, hasLegal, limited-stakes casino gambling]
-
A.
hasLegalRight
Indicates that an entity possesses an officially recognized legal entitlement or permission to perform an action or hold a claim regarding another entity.
-
B.
hasLegalResponse
Indicates that an entity has an associated legal reply, action, or measure taken in response to a legal situation, claim, or requirement.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
-
E.
haveLaw
chosen
Indicates that a governing body or jurisdiction possesses, enforces, or is characterized by a particular law or set of laws.
- 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: April 29, 2026, 7:12 p.m.