Triple
T13128472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Booksellers Association |
E311903
|
entity |
| Predicate | hasMemberBenefit |
P2188
|
FINISHED |
| Object | business resources for bookstores |
—
|
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: business resources for bookstores | Statement: [American Booksellers Association, hasMemberBenefit, business resources for bookstores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberBenefit Context triple: [American Booksellers Association, hasMemberBenefit, business resources for bookstores]
-
A.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
C.
isTopTierBenefit
Indicates that a benefit belongs to the highest or most premium level within a defined benefit hierarchy or structure.
-
D.
isIndividualBenefit
Indicates that something provides a benefit or advantage to a single individual rather than to a group or collective.
-
E.
hasMembershipProgram
Indicates that an entity offers or participates in a structured membership program, typically providing special access, benefits, or services to enrolled members.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819bfd348190a22d44f837877e1c |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.