Triple
T1590232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 World Series |
E34161
|
entity |
| Predicate | championTitleCountForFranchise |
P25122
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [2014 World Series, championTitleCountForFranchise, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championTitleCountForFranchise Context triple: [2014 World Series, championTitleCountForFranchise, 8]
-
A.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
B.
leagueChampionFranchisePennantCount
Indicates the number of league championship pennants won by a given franchise.
-
C.
championRegularSeasonWins
Indicates that an entity is the champion based on having the highest number of regular season wins.
-
D.
hasChampionships
Indicates that one entity possesses or has won one or more championships associated with another entity.
-
E.
hasMostSuccessfulFranchiseByTitles
Indicates that one entity is the franchise holding the highest number of titles (e.g., championships or awards) within a specified domain compared to all other franchises.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93aedd45c819085843ac843d640e8 |
completed | March 5, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69a907bdc19081908c84c5c0aa09e282 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.