Triple
T9909536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China League One |
E185103
|
entity |
| Predicate | usesHeadToHeadTiebreaker |
P6631
|
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, usesHeadToHeadTiebreaker, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesHeadToHeadTiebreaker Context triple: [China League One, usesHeadToHeadTiebreaker, true]
-
A.
fairPlayTiebreakerAffectedTeams
Indicates that the teams involved were impacted by a tiebreaker decision based on fair play criteria (such as disciplinary records).
-
B.
tiebreaker
chosen
Indicates that one entity serves as the deciding factor used to break a tie between two or more otherwise equal options or outcomes.
-
C.
tiebreakerGameLoser
Indicates the player or team that lost a specific tiebreaker game used to resolve a tie in a competition or match.
-
D.
hasTieGame
Indicates that a game or match has ended with both sides having the same score, resulting in no winner.
-
E.
hasSeparateWinnersByLeague
Indicates that winners are determined and recognized separately for each league rather than having a single overall winner.
- 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_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. |
Created at: March 30, 2026, 8:41 p.m.