Triple

T5036919
Position Surface form Disambiguated ID Type / Status
Subject Richard W. Hamming E113447 entity
Predicate notableWork P4 FINISHED
Object 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.
E488672 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: Hamming distance | Statement: [Richard W. Hamming, notableWork, Hamming distance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamming distance
Context triple: [Richard W. Hamming, notableWork, Hamming distance]
  • A. Levenstein
    Levenstein is a surname, often a variant of Löwenstein, borne by individuals of German or Ashkenazi Jewish origin.
  • B. 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.
  • C. Kolmogorov distance
    Kolmogorov distance is a statistical metric that measures the maximum difference between two cumulative distribution functions, commonly used to quantify convergence in distribution and in goodness-of-fit tests.
  • D. Hellinger distance
    Hellinger distance is a statistical measure of dissimilarity between probability distributions, derived from the Euclidean distance between their square-root densities and widely used in probability theory and information geometry.
  • E. 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.
  • 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: Hamming distance
Triple: [Richard W. Hamming, notableWork, Hamming distance]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hamming distance
Target entity description: 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.
  • A. Levenstein
    Levenstein is a surname, often a variant of Löwenstein, borne by individuals of German or Ashkenazi Jewish origin.
  • B. 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.
  • C. Kolmogorov distance
    Kolmogorov distance is a statistical metric that measures the maximum difference between two cumulative distribution functions, commonly used to quantify convergence in distribution and in goodness-of-fit tests.
  • D. Hellinger distance
    Hellinger distance is a statistical measure of dissimilarity between probability distributions, derived from the Euclidean distance between their square-root densities and widely used in probability theory and information geometry.
  • E. 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.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73bb069c8190af86f1b2f95f3d95 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c79265081908512b39cc74161f8 completed March 21, 2026, 1:26 p.m.
NEDg Description generation batch_69be9d517df88190bcd682badaca96c8 completed March 21, 2026, 1:29 p.m.
NED2 Entity disambiguation (via description) batch_69be9dea9de48190805b1e3527b47a00 completed March 21, 2026, 1:32 p.m.
Created at: March 20, 2026, 1:37 p.m.