Triple

T9375029
Position Surface form Disambiguated ID Type / Status
Subject The Searchers E225626 entity
Predicate notableWork P4 FINISHED
Object Sugar and Spice E565795 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: Sugar and Spice | Statement: [The Searchers, notableWork, Sugar and Spice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sugar and Spice
Context triple: [The Searchers, notableWork, Sugar and Spice]
  • A. Sugar & Spice chosen
    Sugar & Spice is a studio album by American R&B singer Mýa that showcases her blend of smooth vocals, contemporary R&B, and pop influences.
  • B. Sweet and Lovely
    "Sweet and Lovely" is a popular jazz and pop standard from the early 1930s that has been widely recorded by numerous vocalists and instrumentalists.
  • C. Sweetie
    Sweetie is a 1989 Australian black comedy-drama film directed by Jane Campion that explores a dysfunctional family through darkly surreal and psychologically intense storytelling.
  • D. Sweetums
    Sweetums is a large, shaggy, ogre-like Muppet character known for his imposing appearance and surprisingly gentle, lovable personality.
  • E. Sugar on a Stick
    Sugar on a Stick is a portable, USB-based distribution of the Sugar learning environment designed to provide children with an easy, bootable educational platform.
  • 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_69ca842d8ee88190aaaa639aa953185d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd50a8b6f48190b77d93a172c54953 completed April 1, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f4229c988190be23ccfae8b350ec completed April 4, 2026, 11:21 a.m.
Created at: March 30, 2026, 7:43 p.m.