Triple

T13678573
Position Surface form Disambiguated ID Type / Status
Subject Andrew Johns E327938 entity
Predicate employerAfterRetirement P33603 FINISHED
Object Nine Network E58646 NE 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: Nine Network | Statement: [Andrew Johns, employerAfterRetirement, Nine Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nine Network
Context triple: [Andrew Johns, employerAfterRetirement, Nine Network]
  • A. Nine Network chosen
    Nine Network is a major Australian commercial television network known for broadcasting popular news, sports, and entertainment programming nationwide.
  • B. Seven Network
    Seven Network is a major Australian commercial free-to-air television network known for broadcasting popular sports, news, and entertainment programming nationwide.
  • C. Network Ten
    Network Ten is a major Australian commercial television network known for broadcasting popular entertainment, news, and sports programming nationwide.
  • D. CW Network
    The CW Network is an American broadcast television network known for airing youth-oriented series, superhero shows, and teen dramas.
  • E. SBS Television
    SBS Television is an Australian free-to-air public broadcasting network known for its multicultural and multilingual programming.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65d8dc081909664e69bb38610ba completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f794405a38819085f38170c56564f2 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.