Triple
T26759196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Espen |
E674751
|
entity |
| Predicate | appliesToSportType |
P180210
|
FINISHED |
| Object | association football |
—
|
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: association football | Statement: [Espen, appliesToSportType, association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToSportType Context triple: [Espen, appliesToSportType, association football]
-
A.
appliesToSports
Indicates that something is relevant, appropriate, or specifically intended for use in the context of sports.
-
B.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
C.
performsForSport
Indicates that an entity carries out an action or activity specifically in the context of a particular sport.
-
D.
appliedToStadiumType
Indicates that something (such as a rule, condition, or attribute) is specifically applied to a particular type or category of stadium.
-
E.
basedOnSport
Indicates that something is determined, derived, or organized according to a particular sport or sporting activity.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 27, 2026, 3:57 a.m.