Triple
T20043490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina and Paraguay |
E497490
|
entity |
| Predicate | shareSportPassion |
P95192
|
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: [Argentina and Paraguay, shareSportPassion, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareSportPassion Context triple: [Argentina and Paraguay, shareSportPassion, football]
-
A.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
B.
shareSportsCulture
chosen
Indicates that two or more entities participate in or identify with the same sports-related traditions, values, or practices.
-
C.
sportsAttraction
Indicates a relationship where an entity serves as a venue, site, or draw specifically for sports-related activities or events.
-
D.
sportCreated
Indicates that an entity is the originator or inventor of a particular sport.
-
E.
popularSport
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662ed59bc8190a9ff25493e500ebb |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:37 p.m.