Triple
T199825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byron Nelson |
E4077
|
entity |
| Predicate | consecutiveWinsInSeason |
P8065
|
FINISHED |
| Object | 11 (1945) |
—
|
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: 11 (1945) | Statement: [Byron Nelson, consecutiveWinsInSeason, 11 (1945)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consecutiveWinsInSeason Context triple: [Byron Nelson, consecutiveWinsInSeason, 11 (1945)]
-
A.
bestSeasonRecord
Indicates that one entity holds the best (most successful) season performance record among a set of entities, typically in a competitive or statistical context.
-
B.
wonStanleyCupInSeason
Indicates that a team secured the Stanley Cup championship title in a specified hockey season.
-
C.
seriesWinningGame
Indicates that a particular game is the decisive or clinching game in which one side wins the overall series.
-
D.
notableSeason
Indicates that a particular season is especially significant or noteworthy in relation to an entity (such as a person, team, or series).
-
E.
mostOverallWinsRecord
Indicates that the subject holds the record for having the greatest total number of wins compared to all others in the relevant context.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25bc6ba208190aa8bec59d32f95fd |
completed | Feb. 28, 2026, 3:06 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.