Triple
T6638154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Bloomer |
E150509
|
entity |
| Predicate | internationalGoalsPerGameRatio |
P71871
|
FINISHED |
| Object | more than 1 goal per game for England |
—
|
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: more than 1 goal per game for England | Statement: [Steve Bloomer, internationalGoalsPerGameRatio, more than 1 goal per game for England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: internationalGoalsPerGameRatio Context triple: [Steve Bloomer, internationalGoalsPerGameRatio, more than 1 goal per game for England]
-
A.
averageGoalsPerMatch
Indicates the typical number of goals scored per match in the context of the given entities or competition.
-
B.
usesGoalAverage
Indicates that one entity determines outcomes or rankings based on the average number of goals scored, typically in a sports or competitive context.
-
C.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
-
E.
worldCupGoals
Indicates the number of goals an entity scored in World Cup matches.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6c30733908190980f7ffaa5c5527b |
completed | March 27, 2026, 5:48 p.m. |
Created at: March 27, 2026, 2 p.m.