Triple

T10168113
Position Surface form Disambiguated ID Type / Status
Subject GSER E235257 entity
Predicate fullName P16 FINISHED
Object Generic String Encoding Rules E564767 NE FINISHED

How this triple was built (2 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: Generic String Encoding Rules | Statement: [GSER, fullName, Generic String Encoding Rules]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Generic String Encoding Rules
Context triple: [GSER, fullName, Generic String Encoding Rules]
  • A. Encoding Standard
    The Encoding Standard is a WHATWG specification that defines how text is encoded and decoded on the web to ensure consistent character handling across browsers and platforms.
  • B. Scott encoding
    Scott encoding is a method in lambda calculus for representing algebraic data types and their pattern matching behavior using higher-order functions.
  • C. Specific Area Message Encoding
    Specific Area Message Encoding (SAME) is a digital protocol used in U.S. emergency alerting systems to target warnings to specific geographic areas and types of hazards.
  • D. Unicode text processing algorithms chosen
    Unicode text processing algorithms are standardized procedures that define how Unicode text is compared, sorted, segmented, normalized, and otherwise manipulated consistently across different systems and languages.
  • E. Speaking in Strings
    Speaking in Strings is a documentary film that explores the life, artistry, and emotional intensity of virtuoso violinist Nadia Salerno-Sonnenberg.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec6f64a48190883aefce58a65ca6 completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300ebacb88190850cf2242309b6ba completed April 6, 2026, 12:40 a.m.
Created at: March 30, 2026, 9:10 p.m.