Triple

T14878793
Position Surface form Disambiguated ID Type / Status
Subject Data E349938 entity
Predicate memberOf P10 FINISHED
Object the Goonies E261219 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: the Goonies | Statement: [Data, memberOf, the Goonies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: the Goonies
Context triple: [Data, memberOf, the Goonies]
  • A. The Goonies chosen
    The Goonies is a 1985 adventure-comedy film about a group of kids who embark on a treasure hunt to save their homes from foreclosure.
  • B. Data in The Goonies
    Data in *The Goonies* is an inventive young member of the Goonies gang known for his homemade gadgets and booby traps that help the group on their adventure.
  • C. The Kid
    "The Kid" is the early-career nickname of NBA Hall of Famer Kevin Garnett, reflecting his youthful energy and precocious talent when he entered the league straight out of high school.
  • D. The Kid
    The Kid is the nickname of Meldrick Taylor, an American former professional boxer known for his exceptional speed and as a two-weight world champion in the 1980s and early 1990s.
  • E. The Kid
    The Kid is a central character in the 2001 Brazilian film "Behind the Sun," representing youthful innocence amid a violent family feud in rural Brazil.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e622388190b2bf91cd10b9821d completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e8192548190ad268b5804c97060 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:55 a.m.