Triple
T25827177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Argus |
E650562
|
entity |
| Predicate | countryOfFictionalPublication |
P44462
|
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: [The Argus, countryOfFictionalPublication, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfFictionalPublication Context triple: [The Argus, countryOfFictionalPublication, United Kingdom]
-
A.
countryOfPublication
Indicates the country in which a work was formally published or made publicly available.
-
B.
countryOfFictionalContext
chosen
Indicates that a work of fiction is primarily set in, or contextually associated with, a particular country.
-
C.
continentOfPublication
Indicates the continent on which the publication was produced or released.
-
D.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
E.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 22, 2026, 7:36 a.m.