Triple

T9909535
Position Surface form Disambiguated ID Type / Status
Subject China League One E185103 entity
Predicate usesGoalDifferenceTiebreaker P91093 FINISHED
Object true 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: true | Statement: [China League One, usesGoalDifferenceTiebreaker, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesGoalDifferenceTiebreaker
Context triple: [China League One, usesGoalDifferenceTiebreaker, true]
  • A. leagueGoalDifference
    Indicates the numerical difference between goals scored and goals conceded by an entity within a league competition.
  • B. usesAwayGoalsRule
    Indicates that a competition or match outcome is decided using the away goals rule, where goals scored by a team in away games serve as a tiebreaker.
  • C. fairPlayTiebreakerAffectedTeams
    Indicates that the teams involved were impacted by a tiebreaker decision based on fair play criteria (such as disciplinary records).
  • D. goalsByLosingTeam
    Indicates the number of goals scored by the team that ultimately lost the match.
  • E. penaltyGoalPoints
    Indicates that points are awarded for a goal scored from a penalty situation.
  • F. None of above. chosen

Provenance (4 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb51184d08190a0350f2722110811 completed April 2, 2026, 12:15 a.m.
PD Predicate disambiguation batch_69cd1d8c584081908b73de75eb18e438 completed April 1, 2026, 1:28 p.m.
PDg Predicate description generation batch_69cd3581a9688190a00cef4c3eebb0ae completed April 1, 2026, 3:10 p.m.
Created at: March 30, 2026, 8:41 p.m.