Triple
T24893917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Women's Euro 2022 |
E623081
|
entity |
| Predicate | attendanceRecordVenue |
P157779
|
FINISHED |
| Object | Wembley Stadium |
—
|
NE NERFINISHED |
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: Wembley Stadium | Statement: [UEFA Women's Euro 2022, attendanceRecordVenue, Wembley Stadium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendanceRecordVenue Context triple: [UEFA Women's Euro 2022, attendanceRecordVenue, Wembley Stadium]
-
A.
attendanceRecordMatch
Indicates that two attendance records correspond to the same underlying event, person, or time entry according to defined matching criteria.
-
B.
recordAttendance
Indicates that an entity documents or logs the presence or participation of another entity at a specific event, session, or time.
-
C.
homeAttendanceRecord
Indicates that an entity’s record or log of attendance is specifically associated with events or activities held at its home venue or location.
-
D.
attendanceUnit
Indicates a unit or measure used to quantify or record attendance in a given context.
-
E.
attendance
Indicates the relationship between an event and the people who are present at or participate in that event.
- 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_69e2fac597708190a922bf39a49ec70a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 5:26 a.m.