Triple
T4212804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Bay Packers–Detroit Lions rivalry |
E93943
|
entity |
| Predicate | team2SuperBowlEraSuccess |
P54778
|
FINISHED |
| Object | limited for Detroit Lions |
—
|
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: limited for Detroit Lions | Statement: [Green Bay Packers–Detroit Lions rivalry, team2SuperBowlEraSuccess, limited for Detroit Lions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: team2SuperBowlEraSuccess Context triple: [Green Bay Packers–Detroit Lions rivalry, team2SuperBowlEraSuccess, limited for Detroit Lions]
-
A.
team2SuperBowlTitles
Indicates the number of Super Bowl championships won by the second team in a given context.
-
B.
team1SuperBowlTitles
Indicates the number of Super Bowl championships that the first team has won.
-
C.
mostSuccessfulTeamBySuperBowls
Indicates that the subject is the team holding the record for the greatest number of Super Bowl victories.
-
D.
hasWonSuperBowlViaTeam
Indicates that an individual has won a Super Bowl specifically as a member of the specified team.
-
E.
SuperBowlWins
Indicates the number of Super Bowl championships that a team or individual has won.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:04 p.m.