Triple
T13869412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arctic Slope Regional Corporation |
E333409
|
entity |
| Predicate | shareholderBenefits |
P487
|
FINISHED |
| Object | dividend distributions |
—
|
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: dividend distributions | Statement: [Arctic Slope Regional Corporation, shareholderBenefits, dividend distributions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareholderBenefits Context triple: [Arctic Slope Regional Corporation, shareholderBenefits, dividend distributions]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
benefitsOperator
Indicates that one entity provides an advantage, profit, or positive outcome to an operator entity.
-
D.
benefitsArea
Indicates that one entity provides advantages, improvements, or positive effects to a specified area or region.
-
E.
benefitCharacteristic
Indicates that one entity possesses a quality or feature that provides an advantage, usefulness, or positive effect to another entity.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:14 p.m.