Triple

T10924845
Position Surface form Disambiguated ID Type / Status
Subject 4chan E258037 entity
Predicate hasPart P35 FINISHED
Object /fit/
/fit/ is 4chan’s fitness board, dedicated to discussions about exercise, bodybuilding, weight loss, nutrition, and general physical self-improvement.
 E894099 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: [4chan, hasPart, /fit/]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: /fit/
Context triple: [4chan, hasPart, /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 a private research university in Melbourne, Florida, known for its strong programs in engineering, science, and aeronautics.
  • C. 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.
  • D. FIT
    FIT is the National Rail station code for Filton Abbey Wood railway station in Bristol, England.
  • E. 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.
  • 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: [4chan, hasPart, /fit/]
Generated description
/fit/ is 4chan’s fitness board, dedicated to discussions about exercise, bodybuilding, weight loss, nutrition, and general physical self-improvement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: /fit/
Target entity description: /fit/ is 4chan’s fitness board, dedicated to discussions about exercise, bodybuilding, weight loss, nutrition, and general physical self-improvement.
  • 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 a private research university in Melbourne, Florida, known for its strong programs in engineering, science, and aeronautics.
  • C. 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.
  • D. FIT
    FIT is the National Rail station code for Filton Abbey Wood railway station in Bristol, England.
  • E. 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.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708f7ab48190b60a4bb8fdb17c8e completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e217369b648190914c58db6f6e0200 completed April 17, 2026, 11:19 a.m.
NEDg Description generation batch_69e21d8a2e6881909b33cbe4ab919315 completed April 17, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_69e21eaa1e9881909f3b276e0ff0c511 completed April 17, 2026, 11:51 a.m.
Created at: April 8, 2026, 9:22 p.m.