Triple

T14861988
Position Surface form Disambiguated ID Type / Status
Subject AFL clubs E349516 entity
Predicate typicalOwnershipModel P21682 FINISHED
Object member-based not-for-profit LITERAL FINISHED

How this triple was built (2 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: member-based not-for-profit | Statement: [AFL clubs, typicalOwnershipModel, member-based not-for-profit]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalOwnershipModel
Context triple: [AFL clubs, typicalOwnershipModel, member-based not-for-profit]
  • A. ownershipType
    Indicates the specific nature or category of the ownership relationship that one entity holds over another.
  • B. ownershipModel chosen
    Indicates the type or structure of ownership relationship that governs how control, rights, or shares are held between entities.
  • C. typicallyOwnedBy
    Indicates that something is most commonly or usually possessed or owned by a particular type of entity.
  • D. typicalUnitType
    Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
  • E. ownershipCharacteristic
    Indicates that one entity possesses a particular quality, attribute, or condition specifically in its role as an owner of another entity.
  • F. None of above.

Provenance (3 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded573cba881908d6d9ac570a64e5f completed April 15, 2026, 12:01 a.m.
PD Predicate disambiguation batch_69de8c1798c08190b433e9ad21e41a42 completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:54 a.m.