Triple
T11346287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuluksak, Alaska |
E268720
|
entity |
| Predicate | economicChallenges |
P24789
|
FINISHED |
| Object | high unemployment |
—
|
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: high unemployment | Statement: [Tuluksak, Alaska, economicChallenges, high unemployment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicChallenges Context triple: [Tuluksak, Alaska, economicChallenges, high unemployment]
-
A.
hasEconomicChallenge
chosen
Indicates that an entity is experiencing or facing a financial or economic difficulty, constraint, or problem.
-
B.
economicSectorIssue
Indicates that there is a problem, challenge, or concern affecting a particular economic sector.
-
C.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
D.
economicView
Indicates a relationship where one entity holds or expresses a particular economic belief, stance, or perspective regarding economic systems, policies, or issues.
-
E.
economicFunction
Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.