Triple
T260704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl XLIX |
E5533
|
entity |
| Predicate | seahawksConsecutiveSuperBowlAppearancesNumber |
P10039
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Super Bowl XLIX, seahawksConsecutiveSuperBowlAppearancesNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seahawksConsecutiveSuperBowlAppearancesNumber Context triple: [Super Bowl XLIX, seahawksConsecutiveSuperBowlAppearancesNumber, 2]
-
A.
SuperBowlAppearances
Indicates the number of times an entity has participated in a Super Bowl game.
-
B.
team2SuperBowlTitles
Indicates the number of Super Bowl championships won by the second team in a given context.
-
C.
team1SuperBowlTitles
Indicates the number of Super Bowl championships that the first team has won.
-
D.
SuperBowlChampionCount
Indicates the number of Super Bowl championships an entity (typically a team or franchise) has won.
-
E.
RamsSuperBowlAppearanceNumber
Indicates the ordinal number of a specific Super Bowl appearance made by the Rams.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b6c968c819094fc903a3a377e15 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e292fdc8190bfd51d8848f9ed58 |
completed | Feb. 28, 2026, 3:16 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.