Triple
T8642830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Zaeem |
E204695
|
entity |
| Predicate | appliedToSport |
P5085
|
FINISHED |
| Object | 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: football | Statement: [Al Zaeem, appliedToSport, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToSport Context triple: [Al Zaeem, appliedToSport, football]
-
A.
appliesToSports
chosen
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.
basedOnSport
Indicates that something is determined, derived, or organized according to a particular sport or sporting activity.
-
D.
alsoUsedForSport
Indicates that something primarily associated with one purpose is additionally used for sporting activities or athletic purposes.
-
E.
usedInSport
Indicates that something (such as an object, technique, or concept) is employed or utilized within the context of a particular sport.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc479720f481908ee2b12c2775e76a |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.