Triple
T3057323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl XLIV |
E60511
|
entity |
| Predicate | hostCityNumberOfSuperBowlsHosted |
P44826
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Super Bowl XLIV, hostCityNumberOfSuperBowlsHosted, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostCityNumberOfSuperBowlsHosted Context triple: [Super Bowl XLIV, hostCityNumberOfSuperBowlsHosted, 10]
-
A.
SuperBowlAppearances
Indicates the number of times an entity has participated in a Super Bowl game.
-
B.
SuperBowlChampionCount
Indicates the number of Super Bowl championships an entity (typically a team or franchise) has won.
-
C.
SuperBowlVenue
Indicates that a location serves as the host venue where a particular Super Bowl game is played.
-
D.
hostStadiumSuperBowlNumberAtVenue
Indicates that a specific stadium served as the host venue for a particular numbered Super Bowl at a given location or venue.
-
E.
homeSuperBowlWin
Indicates that a team won the Super Bowl while playing in its home stadium or home city.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e162d148190969fb422a45d052c |
completed | March 8, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f6af3881909f4547967384114c |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.