Triple
T25623153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonny Bairstow |
E642354
|
entity |
| Predicate | teamNumberOfMatchesType |
P158933
|
FINISHED |
| Object | has played Tests, ODIs and T20Is 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: has played Tests, ODIs and T20Is for England | Statement: [Jonny Bairstow, teamNumberOfMatchesType, has played Tests, ODIs and T20Is for England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamNumberOfMatchesType Context triple: [Jonny Bairstow, teamNumberOfMatchesType, has played Tests, ODIs and T20Is for England]
-
A.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
-
B.
totalMatchesPlayed
Indicates the total number of matches that have been played by the referenced entity or between the related entities.
-
C.
matchesPlayedIn
Indicates that a particular match was played in a specified location, event, or competition context.
-
D.
gameCountPerTeam
Indicates the number of games associated with or played by each team.
-
E.
leagueMatchesPlayed
Indicates the number of matches an entity has participated in within a specific league competition.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa21e21c8190bd06cc3763c6eec3 |
completed | May 2, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 5:06 p.m.