Triple

T2506564
Position Surface form Disambiguated ID Type / Status
Subject myRewards E52597 entity
Predicate rewardRedemption P40855 FINISHED
Object discounts 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: discounts | Statement: [myRewards, rewardRedemption, discounts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rewardRedemption
Context triple: [myRewards, rewardRedemption, discounts]
  • A. rewardUse
    Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
  • B. rewardFulfilledFor
    Indicates that a previously promised or expected reward has been delivered or satisfied for a particular entity.
  • C. redemptionType
    Indicates the manner or method by which something (such as a benefit, reward, or obligation) can be redeemed or fulfilled.
  • D. grantedAsRewardFor
    Indicates that something is given to an entity specifically as a reward for a particular action, achievement, or service.
  • E. rewardSignal
    Indicates that one entity provides a signal representing feedback or incentive (such as a reward or penalty) to guide another entity’s behavior or learning process.
  • F. None of above. chosen

Provenance (4 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_69ab4958e76481908a235377dd921c9e completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd65d6a988190aaaac8e98540a14f completed March 7, 2026, 7:40 a.m.
PD Predicate disambiguation batch_69abd0bd996c8190ba8b9d6e4333b8d4 completed March 7, 2026, 7:16 a.m.
PDg Predicate description generation batch_69abd65c9d508190957285a078698ed2 completed March 7, 2026, 7:40 a.m.
Created at: March 6, 2026, 9:46 p.m.