Triple

T10030550
Position Surface form Disambiguated ID Type / Status
Subject Fashion Institute of Technology E204840 entity
Predicate abbreviation P43 FINISHED
Object FIT
FIT is a renowned New York City-based college specializing in fashion, design, art, business, and technology, and is part of the State University of New York (SUNY) system.
 E836557 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: FIT | Statement: [Fashion Institute of Technology, abbreviation, FIT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FIT
Context triple: [Fashion Institute of Technology, abbreviation, FIT]
  • A. FIT
    FIT is a software testing framework designed to facilitate collaboration between developers and customers by expressing and automatically checking requirements in tabular form.
  • B. FIT
    FIT is the National Rail station code for Filton Abbey Wood railway station in Bristol, England.
  • C. FIT
    FIT is a private research university in Melbourne, Florida, known for its strong programs in engineering, science, and aeronautics.
  • D. The Fit
    The Fit is a literary work by British novelist and critic Philip Hensher, known for his sharp social observation and nuanced character portrayal.
  • E. Fitter
    Fitter is the NATO reporting name for the Soviet-designed Sukhoi Su-17/20/22 family of variable-sweep wing fighter-bomber aircraft.
  • 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: FIT
Triple: [Fashion Institute of Technology, abbreviation, FIT]
Generated description
FIT is a renowned New York City-based college specializing in fashion, design, art, business, and technology, and is part of the State University of New York (SUNY) system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FIT
Target entity description: FIT is a renowned New York City-based college specializing in fashion, design, art, business, and technology, and is part of the State University of New York (SUNY) system.
  • A. FIT
    FIT is a software testing framework designed to facilitate collaboration between developers and customers by expressing and automatically checking requirements in tabular form.
  • B. FIT
    FIT is the National Rail station code for Filton Abbey Wood railway station in Bristol, England.
  • C. FIT
    FIT is a private research university in Melbourne, Florida, known for its strong programs in engineering, science, and aeronautics.
  • D. The Fit
    The Fit is a literary work by British novelist and critic Philip Hensher, known for his sharp social observation and nuanced character portrayal.
  • E. Fitter
    Fitter is the NATO reporting name for the Soviet-designed Sukhoi Su-17/20/22 family of variable-sweep wing fighter-bomber aircraft.
  • 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_69ca834d77188190ad645e33e8ca3200 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcde7ec088190845656cc2529c771 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d282351ebc8190b22bf3964823b0ee completed April 5, 2026, 3:39 p.m.
NEDg Description generation batch_69d282fd10248190a1a0b4573b2065ae completed April 5, 2026, 3:42 p.m.
NED2 Entity disambiguation (via description) batch_69d283d0e1748190a0c65bbaa8e8348e completed April 5, 2026, 3:46 p.m.
Created at: March 30, 2026, 8:54 p.m.