Triple
T10253710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | England vs Fiji (2015 Rugby World Cup) |
E240407
|
entity |
| Predicate | englandBonusPointEarned |
P93219
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [England vs Fiji (2015 Rugby World Cup), englandBonusPointEarned, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: englandBonusPointEarned Context triple: [England vs Fiji (2015 Rugby World Cup), englandBonusPointEarned, true]
-
A.
numberOfEnglandGoals
Indicates the number of goals scored by the England team in a given match or context.
-
B.
scoredFor
Indicates that one entity achieved points or a score on behalf of another entity, such as a player scoring for a team.
-
C.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
D.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
E.
earnsMorePointsThan
Indicates that one entity receives a greater number of points than another entity in a given context or comparison.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d32741888190928b045e2241cfac |
completed | April 7, 2026, 9:49 a.m. |
Created at: April 6, 2026, 11:29 a.m.