Triple
T2118321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1990 World Series |
E43857
|
entity |
| Predicate | runnerUpConsecutiveALTitlesNumber |
P11630
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [1990 World Series, runnerUpConsecutiveALTitlesNumber, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runnerUpConsecutiveALTitlesNumber Context triple: [1990 World Series, runnerUpConsecutiveALTitlesNumber, 3]
-
A.
runnerUpConsecutiveAppearances
chosen
Indicates that an entity has achieved runner-up status in a competition for a specified number of consecutive appearances or editions.
-
B.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence or context.
-
C.
consecutiveWinningSeasons
Indicates that an entity (such as a team or individual) has achieved winning seasons in back-to-back or uninterrupted consecutive years.
-
D.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
-
E.
consecutiveWinsInSeason
Indicates that one entity achieved a specified number of back-to-back victories within a single season.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb3117c081908c5e748a869d1f9f |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.