Triple
T19829268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellowstone Dutton Ranch |
E476411
|
entity |
| Predicate | fictionalEconomicActivity |
P35913
|
FINISHED |
| Object | cattle raising |
—
|
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: cattle raising | Statement: [Yellowstone Dutton Ranch, fictionalEconomicActivity, cattle raising]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalEconomicActivity Context triple: [Yellowstone Dutton Ranch, fictionalEconomicActivity, cattle raising]
-
A.
hasFictionalEconomicActivity
chosen
Indicates that an entity is involved in an economic activity that exists only in a fictional or imaginary context.
-
B.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
C.
fictionalIndustry
Indicates that an entity operates within an industry or sector that exists only in fiction rather than in the real world.
-
D.
fictionalLaborSystem
Indicates a labor or employment system that exists only in fiction, such as in stories, games, or speculative worlds, rather than in real-world economies.
-
E.
fictionalField
Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ccd3748190adeaed9a431f8979 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.