Triple

T1210045
Position Surface form Disambiguated ID Type / Status
Subject WebAssembly System Interface E25977 entity
Predicate abbreviation P43 FINISHED
Object WASI
WASI is a modular system interface designed to let WebAssembly programs safely and portably interact with operating system features like files, networking, and clocks.
 E138279 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: WASI | Statement: [WebAssembly System Interface, abbreviation, WASI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WASI
Context triple: [WebAssembly System Interface, abbreviation, WASI]
  • A. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • B. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • D. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • E. WAI
    WAI (Web Accessibility Initiative) is a World Wide Web Consortium (W3C) program that develops guidelines, resources, and standards to make the web accessible to people with disabilities.
  • 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: WASI
Triple: [WebAssembly System Interface, abbreviation, WASI]
Generated description
WASI is a modular system interface designed to let WebAssembly programs safely and portably interact with operating system features like files, networking, and clocks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WASI
Target entity description: WASI is a modular system interface designed to let WebAssembly programs safely and portably interact with operating system features like files, networking, and clocks.
  • A. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • B. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • D. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • E. WAI
    WAI (Web Accessibility Initiative) is a World Wide Web Consortium (W3C) program that develops guidelines, resources, and standards to make the web accessible to people with disabilities.
  • 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_69a4942b30f08190a91c60573e16b5ef completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bde4670481908c16a3a8c1a54aad completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f419b8c8190ac7642b9b4108df8 completed March 7, 2026, 7:40 p.m.
NEDg Description generation batch_69ac7fce1b788190a133ea6f92c62842 completed March 7, 2026, 7:43 p.m.
NED2 Entity disambiguation (via description) batch_69ac8074334081909ad7a045fc23ea71 completed March 7, 2026, 7:45 p.m.
Created at: March 1, 2026, 7:46 p.m.