Triple
T16531388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Championship |
E401573
|
entity |
| Predicate | oversPerDay |
P57800
|
FINISHED |
| Object | fixed number of overs per day under playing conditions |
—
|
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: fixed number of overs per day under playing conditions | Statement: [County Championship, oversPerDay, fixed number of overs per day under playing conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oversPerDay Context triple: [County Championship, oversPerDay, fixed number of overs per day under playing conditions]
-
A.
countInDayApprox
Indicates an approximate number of times an event or relation occurs within a single day.
-
B.
oversPerSide
chosen
Indicates the number of overs allocated to each side (team or player) in a match or contest.
-
C.
numberOfDailyRoundTrips
Indicates the total count of round-trip journeys performed per day in the described context.
-
D.
overtimePeriodCount
Indicates the number of overtime periods that occurred or are allocated in a given event or context.
-
E.
oversLimit
Indicates that an entity exceeds a specified limit, threshold, or allowed maximum.
- F. None of above.
Provenance (3 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed8075c81908ff47396879abd0c |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.