Triple
T3366395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl XIV |
E70845
|
entity |
| Predicate | PittsburghSteelersSuperBowlTitlesNumber |
P7471
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Super Bowl XIV, PittsburghSteelersSuperBowlTitlesNumber, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PittsburghSteelersSuperBowlTitlesNumber Context triple: [Super Bowl XIV, PittsburghSteelersSuperBowlTitlesNumber, 4]
-
A.
conferenceTitlesWonWithSteelers
Indicates the number of conference titles an entity has won while associated with the Steelers.
-
B.
divisionTitlesWonWithSteelers
Indicates the number of division titles an entity has won while associated with the Steelers.
-
C.
team1SuperBowlTitles
Indicates the number of Super Bowl championships that the first team has won.
-
D.
SuperBowlChampionCount
chosen
Indicates the number of Super Bowl championships an entity (typically a team or franchise) has won.
-
E.
team2SuperBowlTitles
Indicates the number of Super Bowl championships won by the second team in a given context.
- F. None of above.
Provenance (3 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb287a30c8190b4c40091675c94fb |
completed | March 8, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69ada4317e288190ab7d0f66e9dba65f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.