Triple

T11472963
Position Surface form Disambiguated ID Type / Status
Subject River Monsters E271954 entity
Predicate presenter P83 FINISHED
Object Jeremy Wade E927401 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: Jeremy Wade | Statement: [River Monsters, presenter, Jeremy Wade]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremy Wade
Context triple: [River Monsters, presenter, Jeremy Wade]
  • A. Jeremy Wade chosen
    Jeremy Wade is a British biologist and extreme angler best known for investigating legendary freshwater creatures and mysterious fish attacks on the television series "River Monsters."
  • B. Jason Wade
    Jason Wade is an American singer-songwriter best known as the lead vocalist and guitarist of the rock band Lifehouse.
  • C. Kevin Wade
    Kevin Wade is an American screenwriter and television producer best known for writing the film "Working Girl" and creating the TV series "Blue Bloods."
  • D. Jeff Corwin
    Jeff Corwin is an American wildlife biologist and television host best known for his nature and animal conservation programs on channels like Animal Planet and Discovery.
  • E. Jim Wade
    Jim Wade is a central character in the 1934 crime drama film "Manhattan Melodrama," portrayed as an ambitious and principled district attorney whose life and career are intertwined with that of his childhood friend turned gangster.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294b3f388190a587c358313f7260 completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6042507c4819096afc2839fda186d completed April 20, 2026, 10:47 a.m.
Created at: April 8, 2026, 9:35 p.m.