Triple
T5525776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1987 Cricket World Cup |
E144917
|
entity |
| Predicate | topRunScorerRuns |
P65246
|
FINISHED |
| Object | 471 |
—
|
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: 471 | Statement: [1987 Cricket World Cup, topRunScorerRuns, 471]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topRunScorerRuns Context triple: [1987 Cricket World Cup, topRunScorerRuns, 471]
-
A.
seriesWinningRunScoredBy
Indicates that a particular run, scored by a specific player, was the decisive run that clinched a series victory for that player’s team.
-
B.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
C.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
D.
mostWickets
Indicates that the subject holds the record for taking the highest number of wickets in a given cricket context or competition.
-
E.
careerRunsScored
Indicates the total number of runs an entity has scored over the entire duration of their playing career.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f89112c8190b276317fcc2acce0 |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:34 p.m.