Triple
T37277238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Kingdom (work of fiction) |
E924678
|
entity |
| Predicate | commonSettingElement |
P195637
|
FINISHED |
| Object | fictional British towns |
—
|
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: fictional British towns | Statement: [United Kingdom (work of fiction), commonSettingElement, fictional British towns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonSettingElement Context triple: [United Kingdom (work of fiction), commonSettingElement, fictional British towns]
-
A.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
B.
standardSettingFor
Indicates that one entity establishes or defines the norms, criteria, or benchmarks that another entity is expected to follow or be measured against.
-
C.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
D.
sharesMainSetting
chosen
Indicates that two works or entities take place in the same primary location or environment that serves as their main setting.
-
E.
serviceSettings
Indicates the configuration or operational parameters applied to a service in the context of its use or provision.
- 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_69f76eacdd8c819094080d3991e6d37c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff3e1762d8819089a60e402e682817 |
completed | May 9, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69ff3d8c6f308190a0646b1432752eb8 |
completed | May 9, 2026, 1:58 p.m. |
Created at: May 3, 2026, 4:16 p.m.