Triple
T9585940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1941 World Series games |
E231288
|
entity |
| Predicate | winnerFranchiseWorldSeriesTitlesAfterSeries |
P89950
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [1941 World Series games, winnerFranchiseWorldSeriesTitlesAfterSeries, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerFranchiseWorldSeriesTitlesAfterSeries Context triple: [1941 World Series games, winnerFranchiseWorldSeriesTitlesAfterSeries, 9]
-
A.
worldSeriesTitles
Indicates the number of World Series championship titles an entity (typically a baseball team) has won.
-
B.
numberOfWorldSeriesTitles
Indicates the count of World Series championship titles that an entity (typically a baseball team or player) has won.
-
C.
team2WorldSeriesTitlesContext
Indicates that the second team in context has won a specified number of World Series titles.
-
D.
WorldSeriesChampionships
Indicates the number of World Series championship titles that an entity (typically a baseball team or franchise) has won.
-
E.
worldSeriesTitlesThroughYear
Indicates the number of World Series titles an entity has won up to and including a specified year.
- F. None of above. chosen
Provenance (4 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_69ca848161688190a68d514a0a9d5129 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99edc2c08190b67b40f6214d46f1 |
completed | April 1, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69ccd59fd7408190b36831902e3f37f7 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:06 p.m.