Triple

T3453053
Position Surface form Disambiguated ID Type / Status
Subject DVB-T2 E72835 entity
Predicate usesErrorCorrection P22596 FINISHED
Object LDPC
LDPC (Low-Density Parity-Check) is a powerful class of linear error-correcting codes known for near-Shannon-limit performance and widespread use in modern high-throughput communication systems.
E358499 NE FINISHED

How this triple was built (5 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: LDPC | Statement: [DVB-T2, usesErrorCorrection, LDPC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LDPC
Context triple: [DVB-T2, usesErrorCorrection, LDPC]
  • A. Algebraic Coding Theory
    Algebraic Coding Theory is a foundational mathematical text that systematically develops the theory and applications of error-correcting codes using algebraic methods.
  • B. Viterbi algorithm
    The Viterbi algorithm is a dynamic programming method used to find the most likely sequence of hidden states in probabilistic models such as Hidden Markov Models, widely applied in fields like digital communications, speech recognition, and bioinformatics.
  • C. Scott encoding
    Scott encoding is a method in lambda calculus for representing algebraic data types and their pattern matching behavior using higher-order functions.
  • D. OFDM
    OFDM (Orthogonal Frequency-Division Multiplexing) is a digital multi-carrier modulation technique that splits data across many closely spaced orthogonal subcarriers to improve robustness against interference and multipath fading in wireless and wired communication systems.
  • E. Golomb
    Golomb is a station on the Carmelit underground funicular system in Haifa, Israel.
  • 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: LDPC
Triple: [DVB-T2, usesErrorCorrection, LDPC]
Generated description
LDPC (Low-Density Parity-Check) is a powerful class of linear error-correcting codes known for near-Shannon-limit performance and widespread use in modern high-throughput communication systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LDPC
Target entity description: LDPC (Low-Density Parity-Check) is a powerful class of linear error-correcting codes known for near-Shannon-limit performance and widespread use in modern high-throughput communication systems.
  • A. Algebraic Coding Theory
    Algebraic Coding Theory is a foundational mathematical text that systematically develops the theory and applications of error-correcting codes using algebraic methods.
  • B. Viterbi algorithm
    The Viterbi algorithm is a dynamic programming method used to find the most likely sequence of hidden states in probabilistic models such as Hidden Markov Models, widely applied in fields like digital communications, speech recognition, and bioinformatics.
  • C. Scott encoding
    Scott encoding is a method in lambda calculus for representing algebraic data types and their pattern matching behavior using higher-order functions.
  • D. OFDM
    OFDM (Orthogonal Frequency-Division Multiplexing) is a digital multi-carrier modulation technique that splits data across many closely spaced orthogonal subcarriers to improve robustness against interference and multipath fading in wireless and wired communication systems.
  • E. Golomb
    Golomb is a station on the Carmelit underground funicular system in Haifa, Israel.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesErrorCorrection
Context triple: [DVB-T2, usesErrorCorrection, LDPC]
  • A. usesForwardErrorCorrection chosen
    Indicates that one entity applies forward error correction techniques to detect and correct errors in data transmitted to or received from another entity.
  • B. requiresCorrection
    Indicates that something is identified as needing modification, adjustment, or fixing to correct an error or deficiency.
  • C. supportsHardwareCalibration
    Indicates that one entity provides the capability or functionality to perform calibration operations on another entity’s hardware.
  • D. usesScrambling
    Indicates that one entity applies a scrambling process or technique to another entity or to information associated with it.
  • E. hasCheckDigit
    Indicates that an identifier or code includes a calculated check digit used to verify its correctness or integrity.
  • F. None of above.

Provenance (6 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_69ad85b12a908190a1d10a6b03b4f8ae completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbaa2f5ec81909ced93c01e8fe38b completed March 8, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360ef69308190a11f37ddbf3bbc7b completed March 13, 2026, 12:57 a.m.
NEDg Description generation batch_69b361958fd88190bd4a8d9837af6610 completed March 13, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b362310884819082a59ab92fe05fdd completed March 13, 2026, 1:02 a.m.
PD Predicate disambiguation batch_69adae041d588190a84a02bca94adec8 completed March 8, 2026, 5:12 p.m.
Created at: March 8, 2026, 3:16 p.m.