Triple
T8799941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anytime Fitness |
E209378
|
entity |
| Predicate | membershipBenefit |
P2188
|
FINISHED |
| Object | access to multiple club locations |
—
|
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: access to multiple club locations | Statement: [Anytime Fitness, membershipBenefit, access to multiple club locations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: membershipBenefit Context triple: [Anytime Fitness, membershipBenefit, access to multiple club locations]
-
A.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
C.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
D.
benefitAvailableAt
Indicates that a particular benefit can be obtained, accessed, or used at a specified location, time, or context.
-
E.
relatedBenefit
Indicates that one entity provides an advantage, gain, or positive outcome that is connected or attributable 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_69ca836320e48190b5cf585b90a322c4 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb7491c8190bcdb98d6cc003d9e |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:44 p.m.