Triple

T9556727
Position Surface form Disambiguated ID Type / Status
Subject NCAA Playing Rules Oversight Panel E230557 entity
Predicate alsoKnownAs P39 FINISHED
Object PROP
PROP is the acronym for the NCAA Playing Rules Oversight Panel, the body responsible for approving and overseeing playing rules across NCAA sports.
 E806417 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: PROP | Statement: [NCAA Playing Rules Oversight Panel, alsoKnownAs, PROP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PROP
Context triple: [NCAA Playing Rules Oversight Panel, alsoKnownAs, PROP]
  • A. PRO
    PRO is the Professional Referee Organization that manages and develops professional soccer match officials in the United States and Canada.
  • B. POR
    POR is the three-letter FIFA country code used to represent the Portugal national football team in international competitions and rankings.
  • C. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • D. POL
    POL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Poland in international standards and data systems.
  • E. PROF
    PROF is the standard abbreviation for the Division of Professional Relations, an organizational unit focused on issues affecting professional practice and workplace relations.
  • 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: PROP
Triple: [NCAA Playing Rules Oversight Panel, alsoKnownAs, PROP]
Generated description
PROP is the acronym for the NCAA Playing Rules Oversight Panel, the body responsible for approving and overseeing playing rules across NCAA sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PROP
Target entity description: PROP is the acronym for the NCAA Playing Rules Oversight Panel, the body responsible for approving and overseeing playing rules across NCAA sports.
  • A. PRO
    PRO is the Professional Referee Organization that manages and develops professional soccer match officials in the United States and Canada.
  • B. POR
    POR is the three-letter FIFA country code used to represent the Portugal national football team in international competitions and rankings.
  • C. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • D. POL
    POL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Poland in international standards and data systems.
  • E. PROF
    PROF is the standard abbreviation for the Division of Professional Relations, an organizational unit focused on issues affecting professional practice and workplace relations.
  • 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_69ca847d3be8819099c9dad2a7e786f1 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9946c7b8819082f3a4ec4fc979e6 completed April 1, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69d15296303c8190adda4b24036d9390 completed April 4, 2026, 6:04 p.m.
NEDg Description generation batch_69d1539bad8481909f9bd060aa3b651c completed April 4, 2026, 6:08 p.m.
NED2 Entity disambiguation (via description) batch_69d154567f408190a848eea4ca905fb6 completed April 4, 2026, 6:11 p.m.
Created at: March 30, 2026, 8:03 p.m.