Triple

T14363439
Position Surface form Disambiguated ID Type / Status
Subject Good for You E356161 entity
Predicate notableTrack P8087 FINISHED
Object Turf E1095788 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: Turf | Statement: [Good for You, notableTrack, Turf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turf
Context triple: [Good for You, notableTrack, Turf]
  • A. Turf chosen
    "Turf" is a song by the American indie pop band Good for You.
  • B. FieldTurf
    FieldTurf is a brand of synthetic turf designed to mimic natural grass and commonly used in sports stadiums and athletic fields.
  • C. The Large Piece of Turf
    The Large Piece of Turf is a 1503 watercolor study by Albrecht Dürer that meticulously depicts a small patch of wild plants and soil, celebrated as an early masterpiece of realistic nature painting.
  • D. Down the Field
    "Down the Field" is the traditional fight song of Syracuse University, closely associated with the spirit and identity of the Syracuse Orange athletic teams.
  • E. Down the Field
    "Down the Field" is a traditional Rutgers University fight song commonly performed at athletic events to rally school spirit and support for the Scarlet Knights.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fabec088190bd8128371b29e958 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd550ca6b88190b76cd486bdd66fdf completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:15 a.m.