Triple
T4619940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P. League+ |
E100951
|
entity |
| Predicate | averageAttendanceCategory |
P57039
|
FINISHED |
| Object | thousands per game |
—
|
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: thousands per game | Statement: [P. League+, averageAttendanceCategory, thousands per game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageAttendanceCategory Context triple: [P. League+, averageAttendanceCategory, thousands per game]
-
A.
averageAttendanceHigh
Indicates that the typical or mean attendance level for an event, venue, or activity is considered high relative to a defined standard or threshold.
-
B.
averageAttendanceTrend
Indicates how the average attendance changes over time, such as increasing, decreasing, or remaining stable.
-
C.
fanAttendance
Indicates the number or presence of fans attending an event, such as a game, show, or performance.
-
D.
stadiumCapacityApprox
Indicates an approximate number of people that a stadium can accommodate.
-
E.
averageAge
Indicates the mean age value calculated from a group of entities or individuals.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e3e6948190925e2cfad20dcc8c |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522fd5c48190ad2bffc0a5bc9061 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd556b93cc8190ab817d2817109a0b |
completed | March 20, 2026, 2:10 p.m. |
Created at: March 20, 2026, 1:12 p.m.