Triple

T14363426
Position Surface form Disambiguated ID Type / Status
Subject Good for You E356161 entity
Predicate hasSingle P3282 FINISHED
Object Turf
"Turf" is a song by the American indie pop band Good for You.
 E1095788 NE FINISHED

How this triple was built (4 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, hasSingle, Turf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Turf
Context triple: [Good for You, hasSingle, Turf]
  • A. FieldTurf
    FieldTurf is a brand of synthetic turf designed to mimic natural grass and commonly used in sports stadiums and athletic fields.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Down the Field
    "Down the Field" is a traditional fight song closely associated with the University of Tennessee Volunteers and their athletic events.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Turf
Triple: [Good for You, hasSingle, Turf]
Generated description
"Turf" is a song by the American indie pop band Good for You.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Turf
Target entity description: "Turf" is a song by the American indie pop band Good for You.
  • A. FieldTurf
    FieldTurf is a brand of synthetic turf designed to mimic natural grass and commonly used in sports stadiums and athletic fields.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Down the Field
    "Down the Field" is a traditional fight song closely associated with the University of Tennessee Volunteers and their athletic events.
  • F. None of above. chosen

Provenance (5 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_69fd4c4cb0c4819094d59b4b1d43588b completed May 8, 2026, 2:37 a.m.
NEDg Description generation batch_69fd4d912ff08190b3594dd134ef7e40 completed May 8, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69fd4e7e7c508190a42070a2f2b33425 completed May 8, 2026, 2:46 a.m.
Created at: April 10, 2026, 1:15 a.m.