Triple

T16451246
Position Surface form Disambiguated ID Type / Status
Subject UMKC School of Dentistry E399553 entity
Predicate offersDegree P49 FINISHED
Object DDS
DDS is a professional doctoral degree in dentistry that qualifies graduates to practice as licensed dentists.
E1213957 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: [UMKC School of Dentistry, offersDegree, DDS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DDS
Context triple: [UMKC School of Dentistry, offersDegree, 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. DDS
    DDS is the stock ticker symbol for Dillard's, an American department store chain.
  • E. DDD
    DDD is a graphical front-end interface for the GNU Debugger (GDB) that provides a visual environment for debugging programs.
  • 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: [UMKC School of Dentistry, offersDegree, DDS]
Generated description
DDS is a professional doctoral degree in dentistry that qualifies graduates to practice as licensed dentists.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DDS
Target entity description: DDS is a professional doctoral degree in dentistry that qualifies graduates to practice as licensed dentists.
  • 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. DDS
    DDS is the stock ticker symbol for Dillard's, an American department store chain.
  • E. DDD
    DDD is a graphical front-end interface for the GNU Debugger (GDB) that provides a visual environment for debugging programs.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ce06de0819086eea241c6b32223 completed April 18, 2026, 7:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0045979c588190b6f7b249147f3174 completed May 10, 2026, 8:45 a.m.
NEDg Description generation batch_6a00472cdc2881908211045515cd21ee completed May 10, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_6a0047b4b6688190afef52b39788ceae completed May 10, 2026, 8:54 a.m.
Created at: April 10, 2026, 5:10 a.m.