Triple

T3727844
Position Surface form Disambiguated ID Type / Status
Subject DVB-S E78991 entity
Predicate forwardErrorCorrection P22596 FINISHED
Object concatenated Reed-Solomon and convolutional coding LITERAL 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: concatenated Reed-Solomon and convolutional coding | Statement: [DVB-S, forwardErrorCorrection, concatenated Reed-Solomon and convolutional coding]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: forwardErrorCorrection
Context triple: [DVB-S, forwardErrorCorrection, concatenated Reed-Solomon and convolutional coding]
  • 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. errorRecovery
    Indicates that an entity detects a failure or error condition and initiates actions to restore normal or acceptable operation.
  • C. trackingErrorCharacteristic
    Indicates the specific type or nature of the discrepancy between a tracked value and its reference or target over time.
  • D. checksum
    Indicates that a value has been computed from data to verify its integrity or detect errors in transmission or storage.
  • E. requiresCorrection
    Indicates that something is identified as needing modification, adjustment, or fixing to correct an error or deficiency.
  • F. None of above.

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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcaf921bc81908bb347d6b9204670 completed March 8, 2026, 7:16 p.m.
PD Predicate disambiguation batch_69adc0452f5081909c79e114a86cce8c completed March 8, 2026, 6:30 p.m.
Created at: March 8, 2026, 3:34 p.m.