Triple
T6810695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal League |
E156623
|
entity |
| Predicate | attendanceTrend |
P52815
|
FINISHED |
| Object | generally lower than AL and NL |
—
|
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: generally lower than AL and NL | Statement: [Federal League, attendanceTrend, generally lower than AL and NL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendanceTrend Context triple: [Federal League, attendanceTrend, generally lower than AL and NL]
-
A.
attendance
Indicates the relationship between an event and the people who are present at or participate in that event.
-
B.
attendancePromotion
Indicates a relationship where one entity promotes, encourages, or incentivizes attendance at an event, activity, or location for another entity.
-
C.
attendanceAnnounced
Indicates that an official statement has been made about whether and/or how many people will attend an event.
-
D.
attendanceInfluence
Indicates how one entity’s presence or participation affects the attendance level or likelihood of attendance of another entity or group.
-
E.
averageAttendanceTrend
chosen
Indicates how the average attendance changes over time, such as increasing, decreasing, or remaining stable.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30ded6481908fd64611607c610e |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.