Triple
T30118578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilpin County, Colorado |
E765493
|
entity |
| Predicate | currentMajorIndustry |
P86518
|
FINISHED |
| Object | gaming and tourism |
—
|
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: gaming and tourism | Statement: [Gilpin County, Colorado, currentMajorIndustry, gaming and tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentMajorIndustry Context triple: [Gilpin County, Colorado, currentMajorIndustry, gaming and tourism]
-
A.
economicSectorDominant
chosen
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
-
B.
latestMajorOccupation
Indicates the most recent primary job or profession held by an entity.
-
C.
industryStatus
Indicates the current operational or regulatory condition of an entity within its industry (e.g., active, inactive, regulated, or restricted status).
-
D.
isMajorIndustrialEconomy
Indicates that an entity is one of the world’s leading industrialized economies, characterized by large-scale industrial output and significant influence in global economic activity.
-
E.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
- 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_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: April 29, 2026, 7:12 p.m.