Triple
T25904225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Women’s Euro 2022 |
E652705
|
entity |
| Predicate | recordAttendanceForWomenEuroMatch |
P14459
|
FINISHED |
| Object | 87192 |
—
|
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: 87192 | Statement: [UEFA Women’s Euro 2022, recordAttendanceForWomenEuroMatch, 87192]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordAttendanceForWomenEuroMatch Context triple: [UEFA Women’s Euro 2022, recordAttendanceForWomenEuroMatch, 87192]
-
A.
bestUefaWomen’sChampionshipResult
Indicates the highest level of success an entity has achieved in the UEFA Women's Championship competition.
-
B.
recordAttendanceCompetition
chosen
Indicates that an entity records or logs attendance information for a competition or competitive event.
-
C.
setAttendanceRecordForUKIceHockey
Indicates setting or establishing the official attendance record for ice hockey events held in the UK.
-
D.
FIFAWomen'sWorldCupAllTimeTopScorer
Indicates that the subject holds the record for scoring the most goals in the history of the FIFA Women's World Cup.
-
E.
conferenceWomen'sSoccer
Indicates that a women's soccer team participates in or is affiliated with a particular athletic conference.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 22, 2026, 8:26 a.m.