Triple
T25368311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan national rugby union team |
E632862
|
entity |
| Predicate | traditionalStrengthInRegion |
P169888
|
FINISHED |
| Object | Asia |
—
|
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: Asia | Statement: [Japan national rugby union team, traditionalStrengthInRegion, Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalStrengthInRegion Context triple: [Japan national rugby union team, traditionalStrengthInRegion, Asia]
-
A.
regionStrength
Indicates the relative level of influence, power, or dominance that one region holds within a specified context or comparison.
-
B.
historicalStrength
Indicates the relative power, influence, or effectiveness an entity possessed during a specified past period.
-
C.
locatedInTraditionalRegion
Indicates that an entity is situated within a specific traditional or historically recognized region.
-
D.
stateLevelStrength
Indicates the degree of power, capacity, or effectiveness that a state-level entity possesses in performing its functions or exerting influence.
-
E.
strongestSupportRegion
Indicates the region where an entity receives its highest level of support compared to all other regions.
- 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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f688d015908190ad5df37030ecf332 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 21, 2026, 1:38 p.m.