Triple

T3146820
Position Surface form Disambiguated ID Type / Status
Subject Racing Club de France E65783 entity
Predicate hasAlternativeName P39 FINISHED
Object RCF
RCF is a historic French multi-sport club based in Paris, best known for its football and rugby sections.
 E331079 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: RCF | Statement: [Racing Club de France, hasAlternativeName, RCF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RCF
Context triple: [Racing Club de France, hasAlternativeName, RCF]
  • A. RIF
    RIF (Rule Interchange Format) is a W3C standard designed to enable the exchange and interoperability of rules across different Semantic Web systems and rule engines.
  • B. RCM
    RCM is a Canadian Earth observation satellite constellation that uses radar imaging to monitor environmental changes, maritime activity, and national security.
  • C. DRFC
    DRFC is the commonly used abbreviation for Doncaster Rovers Football Club, an English professional football team based in Doncaster, South Yorkshire.
  • D. CFC
    CFC is the abbreviation commonly used for the Combined Forces Command, a joint military headquarters coordinating combined operations.
  • E. CFC
    CFC is the commonly used abbreviation for the United States Court of Federal Claims, a federal court that hears monetary claims against the U.S. government.
  • 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: RCF
Triple: [Racing Club de France, hasAlternativeName, RCF]
Generated description
RCF is a historic French multi-sport club based in Paris, best known for its football and rugby sections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RCF
Target entity description: RCF is a historic French multi-sport club based in Paris, best known for its football and rugby sections.
  • A. RIF
    RIF (Rule Interchange Format) is a W3C standard designed to enable the exchange and interoperability of rules across different Semantic Web systems and rule engines.
  • B. RCM
    RCM is a Canadian Earth observation satellite constellation that uses radar imaging to monitor environmental changes, maritime activity, and national security.
  • C. DRFC
    DRFC is the commonly used abbreviation for Doncaster Rovers Football Club, an English professional football team based in Doncaster, South Yorkshire.
  • D. CFC
    CFC is the commonly used abbreviation for the United States Court of Federal Claims, a federal court that hears monetary claims against the U.S. government.
  • E. CFC
    CFC is the abbreviation commonly used for the Combined Forces Command, a joint military headquarters coordinating combined operations.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada598ccf08190b8817c456f38f2d7 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224f53bbc81908416272cd48af69e completed March 12, 2026, 2:29 a.m.
NEDg Description generation batch_69b225896c4c81909e875a2d357e7bc5 completed March 12, 2026, 2:31 a.m.
NED2 Entity disambiguation (via description) batch_69b225fef06081908dcd8201def1ad95 completed March 12, 2026, 2:33 a.m.
Created at: March 8, 2026, 3:05 p.m.