Triple
T9302629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English First Division 1952–53 |
E223802
|
entity |
| Predicate | championsGoalAverage |
P87965
|
FINISHED |
| Object | 1.516 |
—
|
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: 1.516 | Statement: [English First Division 1952–53, championsGoalAverage, 1.516]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championsGoalAverage Context triple: [English First Division 1952–53, championsGoalAverage, 1.516]
-
A.
rankAllTimeGoals
Indicates a relationship that orders entities based on the total number of goals they have scored across all time.
-
B.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
C.
averageGoalsPerMatch
Indicates the typical number of goals scored per match in the context of the given entities or competition.
-
D.
internationalGoalsPerGameRatio
Indicates the ratio between the number of goals an entity scores in international matches and the number of international games it plays.
-
E.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d34c4c819095a213360747c3a6 |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:36 p.m.