Triple
T20990371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Žitava River region |
E517005
|
entity |
| Predicate | languageOfHistoricalDiplomacy |
P141287
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Žitava River region, languageOfHistoricalDiplomacy, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfHistoricalDiplomacy Context triple: [Žitava River region, languageOfHistoricalDiplomacy, Latin]
-
A.
languageOfHistoricalRecord
Indicates the language in which a given historical record is written or recorded.
-
B.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
-
C.
languageOfHistoricalActivity
chosen
Indicates the language in which a historical activity, event, or action was conducted or recorded.
-
D.
languageOfTreatyAftermath
Indicates the language used in documents, discourse, or arrangements that arise as a consequence of a treaty’s implementation or aftermath.
-
E.
historicalLanguageOfScholarship
Indicates that a language has historically been used as a primary medium of scholarly, academic, or learned communication for a given community, region, or tradition.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fc1ba3d0819080d9d03817a45026 |
completed | April 21, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:49 p.m.