Triple
T16879830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul's Boutique |
E421387
|
entity |
| Predicate | samplingStyle |
P124827
|
FINISHED |
| Object | extensive use of multi-layered samples |
—
|
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: extensive use of multi-layered samples | Statement: [Paul's Boutique, samplingStyle, extensive use of multi-layered samples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: samplingStyle Context triple: [Paul's Boutique, samplingStyle, extensive use of multi-layered samples]
-
A.
samplingDesign
Indicates the method or scheme used to select samples from a population for observation or measurement.
-
B.
samplingSource
Indicates that one entity serves as the origin or provider from which another entity is sampled or drawn.
-
C.
sampleType
Indicates the classification or category of a sample in relation to a broader set of samples or experimental conditions.
-
D.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
E.
sampleNumber
Indicates that an entity is identified or associated with a specific sample number within a set of samples.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7fa96588190837777c401880cb3 |
completed | April 18, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32e2c07b081908c8fee9f5507bb9e |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:29 a.m.