Triple
T32092589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France vs Argentina |
E819634
|
entity |
| Predicate | FranceRegionalAssociation |
P174868
|
FINISHED |
| Object | Six Nations Championship |
—
|
NE NERFINISHED |
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: Six Nations Championship | Statement: [France vs Argentina, FranceRegionalAssociation, Six Nations Championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FranceRegionalAssociation Context triple: [France vs Argentina, FranceRegionalAssociation, Six Nations Championship]
-
A.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
B.
wineRegionPartOf
Indicates that a wine-producing region is geographically or administratively contained within a larger wine region or area.
-
C.
neighboringFrenchDepartments
Indicates that two French administrative departments share a common border and are geographically adjacent to each other.
-
D.
primaryFrenchDestination
Indicates that one entity is the main or most significant travel destination in France for another entity.
-
E.
mainFrenchBorderDepartments
Indicates that the referenced departments are the primary administrative regions of France that share a land border with neighboring countries.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 12:25 a.m.