Triple
T15974900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dillard's |
E387419
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
DDS
DDS is the stock ticker symbol for Dillard's, an American department store chain.
|
E1185646
|
NE FINISHED |
How this triple was built (4 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: [Dillard's, tickerSymbol, DDS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DDS Context triple: [Dillard's, tickerSymbol, DDS]
-
A.
DDS
DDS is the California state agency responsible for overseeing services and supports for individuals with developmental disabilities.
-
B.
DDS
DDS is the state agency in Massachusetts responsible for providing services and supports to individuals with intellectual and developmental disabilities.
-
C.
DDS
DDS (Data Distribution Service) is a real-time, publish–subscribe middleware standard for scalable, high-performance data exchange in distributed systems.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DDS Triple: [Dillard's, tickerSymbol, DDS]
Generated description
DDS is the stock ticker symbol for Dillard's, an American department store chain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DDS Target entity description: DDS is the stock ticker symbol for Dillard's, an American department store chain.
-
A.
DDS
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. chosen
Provenance (5 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572c216c81908f2070d2a87609c2 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe8ce7788190a3e0aefc9a29d58a |
completed | May 9, 2026, 11:09 p.m. |
| NEDg | Description generation | batch_69ffbf50d5fc8190a045846f046e04cf |
completed | May 9, 2026, 11:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffbfb1ed7c81908771dedce172707a |
completed | May 9, 2026, 11:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.