Triple
T6649752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France Football |
E150789
|
entity |
| Predicate | hasInternationalAudience |
P1381
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [France Football, hasInternationalAudience, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalAudience Context triple: [France Football, hasInternationalAudience, yes]
-
A.
hasTargetAudienceRegion
Indicates that something is intended for or directed toward an audience located in a specific geographic region.
-
B.
hasInternationalVersion
Indicates that an entity has a corresponding version or counterpart adapted for use in multiple countries or international contexts.
-
C.
hasInternationalStatus
Indicates that an entity holds a recognized status, role, or standing at the international level rather than being limited to a single country or local jurisdiction.
-
D.
isInternational
Indicates that something has a connection to, involves, or extends across more than one country.
-
E.
hasGlobalReach
chosen
Indicates that an entity’s influence, operations, or impact extends across multiple countries or worldwide.
- 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.