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.