Triple
T11655679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DQS_MAIN |
E277006
|
entity |
| Predicate | accessedBy |
P1985
|
FINISHED |
| Object | Data Quality Client |
E56728
|
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: Data Quality Client | Statement: [DQS_MAIN, accessedBy, Data Quality Client]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Data Quality Client Context triple: [DQS_MAIN, accessedBy, Data Quality Client]
-
A.
Data Quality Services
chosen
Data Quality Services is a SQL Server component that provides tools for defining, managing, and improving the quality and consistency of data through knowledge-based cleansing and matching.
-
B.
Data61
Data61 is an Australian national data science and digital innovation research organization within CSIRO, focused on advanced analytics, cybersecurity, and emerging technologies.
-
C.
Data Quality Working Group
The Data Quality Working Group is a specialist body within the hydrographic community that develops and maintains standards, guidelines, and best practices for assessing and communicating the quality of hydrographic and marine geospatial data.
-
D.
DataPilot
DataPilot is LibreOffice Calc’s pivot table tool for interactively summarizing, analyzing, and reorganizing large data sets.
-
E.
Data
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3cee010819089cffdbefe5a6efb |
completed | April 10, 2026, 7:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee88166900819095063f045be44bed |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 8, 2026, 9:39 p.m.