Triple
T30780913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1923 World Series |
E783808
|
entity |
| Predicate | winningFranchiseWorldSeriesTitleNumber |
P16282
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1923 World Series, winningFranchiseWorldSeriesTitleNumber, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningFranchiseWorldSeriesTitleNumber Context triple: [1923 World Series, winningFranchiseWorldSeriesTitleNumber, 1]
-
A.
numberOfWorldSeriesTitles
chosen
Indicates the count of World Series championship titles that an entity (typically a baseball team or player) has won.
-
B.
worldSeriesTitles
Indicates the number of World Series championship titles an entity (typically a baseball team) has won.
-
C.
WorldSeriesChampionships
Indicates the number of World Series championship titles that an entity (typically a baseball team or franchise) has won.
-
D.
worldSeriesTitlesThroughYear
Indicates the number of World Series titles an entity has won up to and including a specified year.
-
E.
worldSeriesTitleCount
Indicates the number of World Series championships an entity (typically a baseball team or player) has won.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68fe42e448190842c62524baf9abc |
completed | May 2, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:41 p.m.