Triple
T27730617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deals with Gold |
E697420
|
entity |
| Predicate | benefitForSubscribers |
P101952
|
FINISHED |
| Object | reduced prices on digital content |
—
|
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: reduced prices on digital content | Statement: [Deals with Gold, benefitForSubscribers, reduced prices on digital content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitForSubscribers Context triple: [Deals with Gold, benefitForSubscribers, reduced prices on digital content]
-
A.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
B.
benefitAppliesTo
chosen
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
C.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
D.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 27, 2026, 3:11 p.m.