Triple
T899219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish-speaking world |
E19408
|
entity |
| Predicate | hasCommonSport |
P15165
|
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: [Spanish-speaking world, hasCommonSport, association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonSport Context triple: [Spanish-speaking world, hasCommonSport, association football]
-
A.
includesSport
chosen
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
B.
hasEsport
Indicates that an entity is associated with or participates in a specific electronic sports (esports) activity or competition.
-
C.
appliesToSports
Indicates that something is relevant, appropriate, or specifically intended for use in the context of sports.
-
D.
hasAthletics
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
E.
numberOfSports
Indicates the quantity of distinct sports associated with or involved in a given 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad4162848190aa2787b2fa3e6575 |
completed | March 1, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69a4aa979d408190b17ccfde132ea628 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.