Triple
T29101163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sports Interactive |
E736641
|
entity |
| Predicate | hasNotableRegionOfPopularity |
P9666
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [Sports Interactive, hasNotableRegionOfPopularity, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableRegionOfPopularity Context triple: [Sports Interactive, hasNotableRegionOfPopularity, United Kingdom]
-
A.
isPartOfPopularRegion
Indicates that an entity belongs to or is contained within a region that is widely recognized or frequently visited.
-
B.
hasNotablePopulation
Indicates that an entity is recognized for having a significant or noteworthy number of inhabitants or members.
-
C.
lessPopularInRegion
Indicates that one entity is less popular than another within a specified geographic region.
-
D.
hasNotableSettlementRegion
Indicates that an entity has a significant or well-known settlement located within a specified geographic region.
-
E.
primaryRegionOfPopularity
chosen
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69ff779e3f0c8190a861f1e4000fd9d9 |
completed | May 9, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69ff77202638819086e4b9f9c0bc7b31 |
completed | May 9, 2026, 6:04 p.m. |
Created at: April 28, 2026, 11:12 a.m.