Triple
T22069876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gruvbyn |
E545375
|
entity |
| Predicate | hasEconomicRoleCurrent |
P1099
|
FINISHED |
| Object | tourism-based economy |
—
|
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: tourism-based economy | Statement: [Gruvbyn, hasEconomicRoleCurrent, tourism-based economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicRoleCurrent Context triple: [Gruvbyn, hasEconomicRoleCurrent, tourism-based economy]
-
A.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
B.
hasEconomicPosition
Indicates that an entity holds a particular role, status, or standing within an economic system or structure.
-
C.
hasEconomicIdentity
Indicates that an entity possesses a distinct economic role, profile, or characterization within an economic system or context.
-
D.
hasEconomicActor
Indicates that an entity participates in or influences an economic activity, process, or system in the role of an economic actor.
-
E.
hasEconomicActivity
chosen
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1288724e881908b38fe7e56d3b448 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:28 p.m.