Triple
T9061982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Developmental Disabilities Services |
E217145
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | DDS |
E638157
|
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: DDS | Statement: [Developmental Disabilities Services, shortName, DDS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DDS Context triple: [Developmental Disabilities Services, shortName, DDS]
-
A.
DDS
chosen
DDS is the California state agency responsible for overseeing services and supports for individuals with developmental disabilities.
-
B.
DDS
DDS (Data Distribution Service) is a real-time, publish–subscribe middleware standard for scalable, high-performance data exchange in distributed systems.
-
C.
DDS
DDS is the state agency in Massachusetts responsible for providing services and supports to individuals with intellectual and developmental disabilities.
-
D.
DDD
DDD is a graphical front-end interface for the GNU Debugger (GDB) that provides a visual environment for debugging programs.
-
E.
DDD
DDD is a software design approach that focuses on modeling complex business domains in close collaboration with domain experts to guide the structure and behavior of software systems.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ecd352c8190a744579209b2e535 |
completed | April 1, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebf4b9348190a7f01c64098c25f7 |
completed | April 3, 2026, 4:33 p.m. |
Created at: March 30, 2026, 7:11 p.m.