Triple
T36264373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English Premiership |
E892180
|
entity |
| Predicate | typicalMatchPointsSystem |
P204807
|
FINISHED |
| Object | 4 points for a win |
—
|
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: 4 points for a win | Statement: [English Premiership, typicalMatchPointsSystem, 4 points for a win]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMatchPointsSystem Context triple: [English Premiership, typicalMatchPointsSystem, 4 points for a win]
-
A.
matchPointsDraw
Indicates that the entities receive or share an equal number of points as a result of a drawn or tied match.
-
B.
typicalNumberOfMatchesPerSeries
Indicates the usual or standard count of matches that are played within a single series.
-
C.
matingSystem
Indicates the type or pattern of reproductive pairing or mating relationships that typically occurs within a species or population.
-
D.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
E.
typicalMatchDay
Indicates that the relationship or conditions described correspond to what normally happens on a standard or usual match day.
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.