Triple
T10827497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W3C RDF Core Working Group |
E255530
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | SPARQL |
E29603
|
NE 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: SPARQL | Statement: [W3C RDF Core Working Group, influenced, SPARQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SPARQL Context triple: [W3C RDF Core Working Group, influenced, SPARQL]
-
A.
SPARQL
chosen
SPARQL is a semantic query language and protocol used to retrieve and manipulate data stored in Resource Description Framework (RDF) format on the Semantic Web.
-
B.
Blazegraph
Blazegraph is an open-source, high-performance graph database and triplestore engine designed for large-scale RDF data and SPARQL querying.
-
C.
SPARQL Working Group
The SPARQL Working Group is a W3C body responsible for developing and standardizing the SPARQL query language and related technologies for the Semantic Web.
-
D.
OWL 2 QL
OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
-
E.
RDF
RDF (Resource Description Framework) is a standard model for data interchange on the Web that represents information as subject–predicate–object triples to enable structured, machine-readable metadata and knowledge graphs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d2b9f88190b79a7b168d7836c8 |
completed | April 9, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8592d8f08190ac577395ad7cc557 |
completed | April 14, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:19 p.m.