Triple
T37545167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Snell |
E933443
|
entity |
| Predicate | teamNumberOfSuperBowlWin |
P188244
|
FINISHED |
| Object | New York Jets |
—
|
NE NERFINISHED |
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: New York Jets | Statement: [Matt Snell, teamNumberOfSuperBowlWin, New York Jets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamNumberOfSuperBowlWin Context triple: [Matt Snell, teamNumberOfSuperBowlWin, New York Jets]
-
A.
SuperBowlWins
Indicates the number of Super Bowl championships that a team or individual has won.
-
B.
team1SuperBowlTitles
Indicates the number of Super Bowl championships that the first team has won.
-
C.
team2SuperBowlTitles
Indicates the number of Super Bowl championships won by the second team in a given context.
-
D.
homeTeamSuperBowlAppearancesAfterWin
Indicates the number of times the home team appeared in the Super Bowl after a particular win.
-
E.
hasWonSuperBowlViaTeam
Indicates that an individual has won a Super Bowl specifically as a member of the specified 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba5ee00fc81909be7b947a3f95034 |
completed | May 6, 2026, 8:34 p.m. |
Created at: May 3, 2026, 4:17 p.m.