Triple
T24344706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Rangers vs. Arizona Diamondbacks |
E613606
|
entity |
| Predicate | RangersPennant |
P2602
|
FINISHED |
| Object | 2023 American League champion |
—
|
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: 2023 American League champion | Statement: [Texas Rangers vs. Arizona Diamondbacks, RangersPennant, 2023 American League champion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RangersPennant Context triple: [Texas Rangers vs. Arizona Diamondbacks, RangersPennant, 2023 American League champion]
-
A.
rangersConsecutiveALPennantsNumber
Indicates the number of consecutive American League pennants won by the Texas Rangers.
-
B.
pennantTeam
chosen
Indicates that a team has won or represents the league or conference pennant for a given season or competition.
-
C.
leaguePennant
Indicates that a team has won the championship pennant for a particular league or season.
-
D.
leaguePennants
Indicates that a team has won a specified number of league pennants (championship titles) in a particular league.
-
E.
mostPennantsTeam
Indicates that the subject is the team that has won the greatest number of league pennants within a specified context or league.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29328b0288190a580939e8863b0c2 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:58 a.m.