Triple
T33431651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brighton Miracle |
E856145
|
entity |
| Predicate | JapanPreviousLargestWorldCupDefeatScore |
P180092
|
FINISHED |
| Object | 145–17 |
—
|
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: 145–17 | Statement: [Brighton Miracle, JapanPreviousLargestWorldCupDefeatScore, 145–17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapanPreviousLargestWorldCupDefeatScore Context triple: [Brighton Miracle, JapanPreviousLargestWorldCupDefeatScore, 145–17]
-
A.
JapanPreviousWorldCupWinOpponent
Indicates the opposing team that Japan defeated in its most recent prior FIFA World Cup victory.
-
B.
JapanPreviousWorldCupWinYear
Indicates the year in which Japan most recently won the FIFA World Cup prior to a given reference point.
-
C.
JapanWorldCupWinsBeforeMatch
Indicates the number of World Cup victories Japan had achieved prior to the referenced match.
-
D.
largestWorldCupDefeatOpponent
Indicates the opposing team against which an entity suffered its largest margin of defeat in a FIFA World Cup match.
-
E.
largestWorldCupDefeatYear
Indicates the year in which an entity experienced its largest defeat in a World Cup match.
- 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_69f349709e7881908c342b4d34f555f4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: May 1, 2026, 1:36 a.m.