Triple
T18568836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICC World Cup Super League |
E453825
|
entity |
| Predicate | pointsForTie |
P132576
|
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, pointsForTie, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsForTie Context triple: [ICC World Cup Super League, pointsForTie, 5]
-
A.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
B.
tiebreaker
Indicates that one entity serves as the deciding factor used to break a tie between two or more otherwise equal options or outcomes.
-
C.
fairPlayTiebreakerAffectedTeams
Indicates that the teams involved were impacted by a tiebreaker decision based on fair play criteria (such as disciplinary records).
-
D.
hasTieGame
Indicates that a game or match has ended with both sides having the same score, resulting in no winner.
-
E.
usesHeadToHeadAsTiebreaker
Indicates that a head-to-head comparison between entities is used to break a tie in their ranking or outcome.
- 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.