Triple
T11273876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crack (football) |
E266880
|
entity |
| Predicate | usedInMatches |
P40885
|
FINISHED |
| Object | World Cup matches |
—
|
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: World Cup matches | Statement: [Crack (football), usedInMatches, World Cup matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInMatches Context triple: [Crack (football), usedInMatches, World Cup matches]
-
A.
usedInMatch
chosen
Indicates that something (such as an item, tactic, or resource) was employed or utilized during a particular match or game.
-
B.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
C.
usedInLeague
Indicates that an entity (such as a team, player, or item) participates or is employed within a particular league.
-
D.
usesMatchesFrom
Indicates that one entity relies on or incorporates matches (e.g., pattern matches, rule matches, or result matches) produced by another entity or process.
-
E.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e965c9048190804ebb48f0a4817b |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:31 p.m.