Triple
T780532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midwest Region |
E16485
|
entity |
| Predicate | hasTopSeed |
P6982
|
FINISHED |
| Object | No. 1 seed |
—
|
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: No. 1 seed | Statement: [Midwest Region, hasTopSeed, No. 1 seed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTopSeed Context triple: [Midwest Region, hasTopSeed, No. 1 seed]
-
A.
hasSeedCount
Indicates that an entity possesses a specific number of seeds.
-
B.
hasSeeding
chosen
Indicates that an entity is assigned or associated with a specific seeding position or rank, typically for ordering or placement in a competitive or structured context.
-
C.
isToppedWith
Indicates that one entity serves as a topping placed on the surface of another entity.
-
D.
usesSeeding
Indicates that an entity employs a seeding process or strategy to initiate, distribute, or propagate something (such as data, content, or resources).
-
E.
determinesSeedingFor
Indicates that one entity is used to decide or assign the ranking, placement, or initial position (seeding) of another entity within a structured order or competition.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a90365648190ace53b0f0e87aa68 |
completed | March 1, 2026, 9 p.m. |
| PD | Predicate disambiguation | batch_69a4a50bd23081908908235b8ec9201e |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.