Triple

T36390868
Position Surface form Disambiguated ID Type / Status
Subject Premier Handicap E896322 entity
Predicate goalOfHandicapper P72446 FINISHED
Object to create a theoretically level playing field 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: to create a theoretically level playing field | Statement: [Premier Handicap, goalOfHandicapper, to create a theoretically level playing field]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: goalOfHandicapper
Context triple: [Premier Handicap, goalOfHandicapper, to create a theoretically level playing field]
  • A. wagerGoal
    Indicates that an entity sets or specifies a target outcome or objective for a wager or bet.
  • B. handicap
    Indicates that one entity imposes or experiences a disadvantage, constraint, or limiting condition in relation to another entity or context.
  • C. handicapOrConditions
    Indicates that there are specific handicaps, constraints, or special conditions that apply to the related entities or their interaction.
  • D. goalType chosen
    Indicates the specific category or nature of a goal associated with an entity or action.
  • E. goalIn
    Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or context.
  • 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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7be9d07ac8190adf796cbef60daf6 completed May 3, 2026, 9:31 p.m.
PD Predicate disambiguation batch_69f7bcccd7988190aa5c931ff347d33c completed May 3, 2026, 9:23 p.m.
Created at: May 3, 2026, 4:10 p.m.