Triple
T18568837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICC World Cup Super League |
E453825
|
entity |
| Predicate | pointsForNoResult |
P132577
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [ICC World Cup Super League, pointsForNoResult, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsForNoResult Context triple: [ICC World Cup Super League, pointsForNoResult, 5]
-
A.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
B.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
C.
pointsScored
Indicates the number of points an entity has earned or achieved in a particular event, game, or context.
-
D.
votingResultHouseNoVotes
Indicates the number or record of "no" votes cast in a voting result within a legislative house.
-
E.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b0075a08190a5d590d36089ca1e |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:43 a.m.