Triple
T37815375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sygun Copper Mine area |
E942758
|
entity |
| Predicate | primaryEconomicRolePresent |
P2223
|
FINISHED |
| Object | 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: tourism | Statement: [Sygun Copper Mine area, primaryEconomicRolePresent, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryEconomicRolePresent Context triple: [Sygun Copper Mine area, primaryEconomicRolePresent, tourism]
-
A.
hasEconomicRole
chosen
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
B.
primaryRoleFor
Indicates that one entity serves as the main or most important role or function for another entity.
-
C.
socioeconomicRole
Indicates the social and economic position, function, or status an entity holds within a society or system.
-
D.
primaryContributionOf
Indicates that one entity is the main or most significant contribution made by another entity.
-
E.
hasPrimarySectorEmployment
Indicates that an entity is employed in the primary economic sector (e.g., agriculture, mining, forestry, or related extractive activities).
- 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_69f76ee987588190906506e759be5db3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.