Triple
T22870965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Regional |
E567192
|
entity |
| Predicate | hasNumberOfRegionalsInTournament |
P103706
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [West Regional, hasNumberOfRegionalsInTournament, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRegionalsInTournament Context triple: [West Regional, hasNumberOfRegionalsInTournament, 4]
-
A.
totalTeamsInRegionals
Indicates the total number of teams that participate in the regional-level stage of a competition or event.
-
B.
regionalsNumber
chosen
Indicates the number of regional-level instances (such as events, competitions, or units) associated with an entity.
-
C.
numberOfTournaments
Indicates the total count of tournaments associated with or participated in by an entity.
-
D.
roundsPerTournament
Indicates the number of rounds that occur within a single tournament.
-
E.
notableTournamentRegion
Indicates that a tournament is notably associated with, recognized in, or significant within a particular geographic region.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f04b06481909004818ec8fc5a26 |
completed | April 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:38 p.m.