Triple

T19455021
Position Surface form Disambiguated ID Type / Status
Subject Hawkins kids and teens group E486712 entity
Predicate hasMember P10 FINISHED
Object Jim Hopper NE NERFINISHED

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: Jim Hopper | Statement: [Hawkins kids and teens group, hasMember, Jim Hopper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jim Hopper
Context triple: [Hawkins kids and teens group, hasMember, Jim Hopper]
  • A. Jim Hopper chosen
    Jim Hopper is a gruff but deeply caring small-town police chief who becomes a central protector of the children and supernatural secrets in the series "Stranger Things."
  • B. James Hopper
    James Hopper is the full given name of Jim Hopper, the fictional small-town police chief from the television series "Stranger Things."
  • C. Trader Horn
    Trader Horn is a 1931 adventure film set in Africa, notable as one of the earliest major studio sound films shot largely on location.
  • D. Nathan Shay
    Nathan Shay is a musician best known for his early involvement as a former member of the Kansas City emo and indie rock band The Get Up Kids.
  • E. Captain Grimes
    Captain Grimes is a roguish, hard-drinking schoolmaster and recurring comic antihero in Evelyn Waugh’s novel "Decline and Fall."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c2b1108190b492ca23487b91f8 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.