Triple

T15926176
Position Surface form Disambiguated ID Type / Status
Subject Exascale Computing Project E386209 entity
Predicate hasAbbreviation P43 FINISHED
Object ECP
ECP is a U.S. Department of Energy initiative focused on developing exascale computing capabilities, including hardware, software, and applications for next-generation high-performance computing.
 E1185342 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: ECP | Statement: [Exascale Computing Project, hasAbbreviation, ECP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ECP
Context triple: [Exascale Computing Project, hasAbbreviation, ECP]
  • A. ECP
    ECP is a fundamental syntactic constraint in generative grammar that governs where empty categories (such as traces) can appear in sentence structure.
  • B. ECP
    ECP is a commercial airport serving the Panama City, Florida area and the surrounding Gulf Coast region.
  • C. ECP
    ECP is the stock ticker symbol for EuropaCorp, a French film studio and production company founded by filmmaker Luc Besson.
  • D. ECP
    ECP is Pakistan’s independent constitutional body responsible for organizing and overseeing national and provincial elections.
  • E. ECPD
    ECPD is the former name of ABET, the primary U.S. organization responsible for accrediting college and university programs in applied science, computing, engineering, and engineering technology.
  • 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: ECP
Triple: [Exascale Computing Project, hasAbbreviation, ECP]
Generated description
ECP is a U.S. Department of Energy initiative focused on developing exascale computing capabilities, including hardware, software, and applications for next-generation high-performance computing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ECP
Target entity description: ECP is a U.S. Department of Energy initiative focused on developing exascale computing capabilities, including hardware, software, and applications for next-generation high-performance computing.
  • A. ECP
    ECP is a fundamental syntactic constraint in generative grammar that governs where empty categories (such as traces) can appear in sentence structure.
  • B. ECP
    ECP is Pakistan’s independent constitutional body responsible for organizing and overseeing national and provincial elections.
  • C. ECP
    ECP is a commercial airport serving the Panama City, Florida area and the surrounding Gulf Coast region.
  • D. ECP
    ECP is the stock ticker symbol for EuropaCorp, a French film studio and production company founded by filmmaker Luc Besson.
  • E. ECPD
    ECPD is the former name of ABET, the primary U.S. organization responsible for accrediting college and university programs in applied science, computing, engineering, and engineering technology.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156866de48190a744e8dcaa0c66f1 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5adcde88190ae2a845aaa9d31ac completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb6c4a66c8190bba70da71c9ec576 completed May 9, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7a373d88190a2fcf75022f3e161 completed May 9, 2026, 10:39 p.m.
Created at: April 10, 2026, 4:52 a.m.