Triple
T26345681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semantic Web agents |
E662771
|
entity |
| Predicate | usedInApplicationArea |
P25490
|
FINISHED |
| Object | e-commerce |
—
|
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: e-commerce | Statement: [Semantic Web agents, usedInApplicationArea, e-commerce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInApplicationArea Context triple: [Semantic Web agents, usedInApplicationArea, e-commerce]
-
A.
usedInPractice
Indicates that something is actually applied or implemented in real-world practice rather than just being theoretical or proposed.
-
B.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
C.
usedInEnvironment
Indicates that something is utilized or operates within a particular environment or context.
-
D.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
E.
usedInIndustry
Indicates that something is employed or applied within a particular industry or industrial sector.
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 26, 2026, 10:42 p.m.