Triple
T25534926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Kids+ |
E640016
|
entity |
| Predicate | hasDifferentPlans |
P168889
|
FINISHED |
| Object | single-child plan |
—
|
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: single-child plan | Statement: [Amazon Kids+, hasDifferentPlans, single-child plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferentPlans Context triple: [Amazon Kids+, hasDifferentPlans, single-child plan]
-
A.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
B.
numberOfPlans
Indicates the quantity or count of plans associated with a given entity or context.
-
C.
hasRelatedPlan
Indicates that one entity is associated with another entity through a plan that is relevant or connected to it.
-
D.
hasTypicalPlan
Indicates that there is a standard or commonly followed plan, procedure, or course of action typically associated with the given entity or situation.
-
E.
hasDifferentBenefitsThan
Indicates that the benefits provided by one entity are not the same as those provided by another entity.
- 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_69e75dbfff7081909b0aa779d48321d2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f67866e9248190b7ba218f9ca2ae8d |
completed | May 2, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 21, 2026, 3:22 p.m.