Triple

T9839905
Position Surface form Disambiguated ID Type / Status
Subject Max Renn E239193 entity
Predicate channelSpecialization P90272 FINISHED
Object sex and violence programming 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: sex and violence programming | Statement: [Max Renn, channelSpecialization, sex and violence programming]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: channelSpecialization
Context triple: [Max Renn, channelSpecialization, sex and violence programming]
  • A. hasSpecialtyChannel
    Indicates that one entity provides or is associated with a dedicated channel focused on a particular specialty or subject area for another entity.
  • B. channels
    Indicates that one entity serves as a medium, route, or conduit through which another entity is directed, transmitted, or delivered.
  • C. typicalChannel
    Indicates the usual or most commonly used communication or distribution channel through which an interaction, message, or transaction typically occurs.
  • D. ownedChannel
    Indicates that one entity possesses ownership or control over a particular channel.
  • E. notableChannel
    Indicates that a channel is recognized as particularly significant, prominent, or noteworthy in some context.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34b045481908f89abd576aab497 completed April 2, 2026, 12:07 a.m.
PD Predicate disambiguation batch_69cd03e30bc08190816c0a6d29c21b0f completed April 1, 2026, 11:39 a.m.
PDg Predicate description generation batch_69cd06abc9248190a506b64e9c516d03 completed April 1, 2026, 11:51 a.m.
Created at: March 30, 2026, 8:33 p.m.