Triple
T15473408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I liga |
E376720
|
entity |
| Predicate | usesGoalDifferenceAsTiebreaker |
P91093
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [I liga, usesGoalDifferenceAsTiebreaker, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGoalDifferenceAsTiebreaker Context triple: [I liga, usesGoalDifferenceAsTiebreaker, yes]
-
A.
usesGoalDifferenceTiebreaker
chosen
Indicates that when entities are tied, their ranking or outcome is decided based on the difference between goals scored and goals conceded.
-
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.
leagueGoalDifference
Indicates the numerical difference between goals scored and goals conceded by an entity within a league competition.
-
D.
fairPlayTiebreakerAffectedTeams
Indicates that the teams involved were impacted by a tiebreaker decision based on fair play criteria (such as disciplinary records).
-
E.
tiebreaker
Indicates that one entity serves as the deciding factor used to break a tie between two or more otherwise equal options or outcomes.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6c57308190b4cfe661c26addd4 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:33 a.m.