Triple
T1087544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonny Jurgensen |
E24085
|
entity |
| Predicate | careerGamesStarted |
P24094
|
FINISHED |
| Object | 147 |
—
|
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: 147 | Statement: [Sonny Jurgensen, careerGamesStarted, 147]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerGamesStarted Context triple: [Sonny Jurgensen, careerGamesStarted, 147]
-
A.
gamesPlayed
Indicates the number or set of games that an entity has participated in or completed.
-
B.
completeGames
Indicates that an entity has finished participating in or playing a game from start to end.
-
C.
consecutiveGamesPlayed
Indicates that an entity has participated in a series of games without interruption, one immediately following another.
-
D.
allStarAppearances
Indicates the number of times an entity has been selected to participate in an All-Star event or game.
-
E.
playedEntireCareerForSingleFranchise
Indicates that an athlete spent their entire professional career playing for only one franchise or team.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7407914819092ed933a7316b450 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8f1097881908932d7eea4331917 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:42 p.m.