Triple
T886989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl LV |
E19150
|
entity |
| Predicate | hasLimitedAttendance |
P99
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Super Bowl LV, hasLimitedAttendance, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLimitedAttendance Context triple: [Super Bowl LV, hasLimitedAttendance, true]
-
A.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
B.
hasLimitation
chosen
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
C.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
D.
isLimitOf
Indicates that one quantity, function, or sequence approaches a particular value as its input or index approaches some specified point or condition.
-
E.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ae787bf081909533082ca013624a |
completed | March 1, 2026, 9:24 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8ff8c48190a33b00acf65c1276 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.