Triple

T28711327
Position Surface form Disambiguated ID Type / Status
Subject APT E729838 entity
Predicate imageEncoding P166236 FINISHED
Object line-by-line analog video 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: line-by-line analog video | Statement: [APT, imageEncoding, line-by-line analog video]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: imageEncoding
Context triple: [APT, imageEncoding, line-by-line analog video]
  • A. imageEncoderType
    Indicates the specific kind or configuration of encoder used to process and represent image data.
  • B. colorEncoding
    Indicates how the color information of an entity is represented, formatted, or encoded.
  • C. colorEncodingMethod
    Indicates the method or scheme used to represent or encode color information.
  • D. videoEncoding
    Indicates that one entity is used to encode, compress, or transform video data into a particular digital format or representation for another entity.
  • E. encodingLibrary
    Indicates that one entity is the software library or tool used to encode, transform, or serialize the other entity’s data or content.
  • F. None of above. chosen

Provenance (4 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_69f043e7d5a4819094b18aca10b1e024 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f66003a3f48190a2ba6da5aafbb5cb completed May 2, 2026, 8:35 p.m.
PD Predicate disambiguation batch_69f65c2198208190a3954086c22cfcbf completed May 2, 2026, 8:18 p.m.
PDg Predicate description generation batch_69f65f75ac608190a62cd6afce14f68e completed May 2, 2026, 8:32 p.m.
Created at: April 28, 2026, 5:48 a.m.