Triple
T412529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivy League Men’s Basketball Tournament |
E9519
|
entity |
| Predicate | tieBreakerBasis |
P6631
|
FINISHED |
| Object | Ivy League regular-season tiebreaker procedures |
—
|
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: Ivy League regular-season tiebreaker procedures | Statement: [Ivy League Men’s Basketball Tournament, tieBreakerBasis, Ivy League regular-season tiebreaker procedures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieBreakerBasis Context triple: [Ivy League Men’s Basketball Tournament, tieBreakerBasis, Ivy League regular-season tiebreaker procedures]
-
A.
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.
-
B.
rankingBasis
Indicates the criterion or standard used to determine the order or rank of entities in a ranking.
-
C.
calculationBasis
Indicates the rule, method, or reference standard used as the foundation for performing a calculation in the relationship.
-
D.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
-
E.
brakeType
Indicates the specific kind or system of brakes associated with an 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecdafa2481908111accc918ff2e8 |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e9749234819084b0ce94faabd0b1 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.