Triple

T19531776
Position Surface form Disambiguated ID Type / Status
Subject Hamming distance E488672 entity
Predicate relatedTo P37 FINISHED
Object Levenshtein distance — NE NERFINISHED

How this triple was built (3 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: Levenshtein distance | Statement: [Hamming distance, relatedTo, Levenshtein distance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Levenshtein distance
Context triple: [Hamming distance, relatedTo, Levenshtein distance]
  • A. Levenstein
    Levenstein is a surname, often a variant of Löwenstein, borne by individuals of German or Ashkenazi Jewish origin.
  • B. Hamming distance
    Hamming distance is a measure in information theory and computer science that counts the number of positions at which corresponding symbols in two equal-length strings differ, widely used in error detection and coding theory.
  • C. Difference Engine
    The Difference Engine is an early mechanical calculator designed by Charles Babbage to automatically compute and tabulate polynomial functions, often regarded as a precursor to modern computers.
  • D. Bhattacharyya distance
    Bhattacharyya distance is a statistical measure of similarity between two probability distributions, often used in pattern recognition and classification to quantify their overlap.
  • E. Bhattacharyya coefficient
    The Bhattacharyya coefficient is a statistical measure of similarity between two probability distributions, often used to quantify their overlap in fields like pattern recognition and signal processing.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Levenshtein distance
Target entity description: Levenshtein distance is a string metric that measures the minimum number of single-character insertions, deletions, and substitutions required to transform one string into another.
  • A. Levenstein
    Levenstein is a surname, often a variant of Löwenstein, borne by individuals of German or Ashkenazi Jewish origin.
  • B. Hamming distance
    Hamming distance is a measure in information theory and computer science that counts the number of positions at which corresponding symbols in two equal-length strings differ, widely used in error detection and coding theory.
  • C. Difference Engine
    The Difference Engine is an early mechanical calculator designed by Charles Babbage to automatically compute and tabulate polynomial functions, often regarded as a precursor to modern computers.
  • D. Bhattacharyya distance
    Bhattacharyya distance is a statistical measure of similarity between two probability distributions, often used in pattern recognition and classification to quantify their overlap.
  • E. Bhattacharyya coefficient
    The Bhattacharyya coefficient is a statistical measure of similarity between two probability distributions, often used to quantify their overlap in fields like pattern recognition and signal processing.
  • F. None of above. chosen

Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6363fd1f8819080805346efad2579 completed April 20, 2026, 2:20 p.m.
Created at: April 10, 2026, 1:41 p.m.