Triple
T30784876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chronicon terrae Prussiae |
E783930
|
entity |
| Predicate | countryOfTopic |
P115399
|
FINISHED |
| Object | Prussia |
—
|
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: Prussia | Statement: [Chronicon terrae Prussiae, countryOfTopic, Prussia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfTopic Context triple: [Chronicon terrae Prussiae, countryOfTopic, Prussia]
-
A.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
-
B.
countryOfSubjectMatter
chosen
Indicates the country that the subject matter (e.g., a work, topic, or issue) primarily concerns or is associated with.
-
C.
countryOn
Indicates that one country is located on or occupies the territory of another geographic entity (such as a larger region, continent, or island).
-
D.
countryIn
Indicates that one entity is geographically or politically located within the boundaries of a specified country.
-
E.
mainCountry
Indicates that one country is the primary or most significant country associated with a given entity or context.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ffac35ac5481908b6bdfd5bbe8c76e |
completed | May 9, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69ffabbfd2548190964c851496bbbaee |
completed | May 9, 2026, 9:48 p.m. |
Created at: April 29, 2026, 8:41 p.m.