Triple
T3758968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Library of Congress Linked Data Service |
E82115
|
entity |
| Predicate | usesStandard |
P1587
|
FINISHED |
| Object | MADS/RDF |
E29602
|
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: MADS/RDF | Statement: [Library of Congress Linked Data Service, usesStandard, MADS/RDF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MADS/RDF Context triple: [Library of Congress Linked Data Service, usesStandard, MADS/RDF]
-
A.
RDFS
RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
-
B.
MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
-
C.
MADOC
MADOC is the state agency responsible for overseeing and managing the prison and correctional system in Massachusetts.
-
D.
RDF
chosen
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.
-
E.
RDA
RDA (Resource Description and Access) is a modern international cataloguing standard used by libraries to describe and provide access to information resources in both digital and physical formats.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc20b20819095fedf803aadc53a |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5133ba48190a18ea170e3b9e1cd |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:35 p.m.