Triple

T1717227
Position Surface form Disambiguated ID Type / Status
Subject DuPont E37316 entity
Predicate tickerSymbol P1447 FINISHED
Object DD
DD is the stock ticker symbol for DuPont, a major American chemicals and materials company known for innovations such as nylon, Kevlar, and Teflon.
 E192832 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: DD | Statement: [DuPont, tickerSymbol, DD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DD
Context triple: [DuPont, tickerSymbol, DD]
  • A. DD
    DD is the official vehicle registration code assigned to the Indian union territory of Dadra and Nagar Haveli and Daman and Diu.
  • B. DDF
    DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
  • C. DiDi
    DiDi is a major Chinese ride-hailing and mobility technology company that operates a platform for on-demand transportation and related services.
  • D. DY
    DY is the IATA airline designator used by Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • E. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • 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: DD
Triple: [DuPont, tickerSymbol, DD]
Generated description
DD is the stock ticker symbol for DuPont, a major American chemicals and materials company known for innovations such as nylon, Kevlar, and Teflon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DD
Target entity description: DD is the stock ticker symbol for DuPont, a major American chemicals and materials company known for innovations such as nylon, Kevlar, and Teflon.
  • A. DD
    DD is the official vehicle registration code assigned to the Indian union territory of Dadra and Nagar Haveli and Daman and Diu.
  • B. DDF
    DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
  • C. DiDi
    DiDi is a major Chinese ride-hailing and mobility technology company that operates a platform for on-demand transportation and related services.
  • D. DY
    DY is the IATA airline designator used by Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • E. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • 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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa63362ba481909e08e9f6fbf00b37 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ae6940c81909c1ebdfb0cdef5fc completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957adf1c8190b7c8656c1984f998 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97af6b388190b2af293599108df3 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.