Triple
T26057689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamburg (Kingisepp) |
E657166
|
entity |
| Predicate | languageOfHistoricalToponym |
P52208
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Yamburg (Kingisepp), languageOfHistoricalToponym, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfHistoricalToponym Context triple: [Yamburg (Kingisepp), languageOfHistoricalToponym, German]
-
A.
languageOfHistoricName
chosen
Indicates the language in which a historic or former name of an entity is expressed.
-
B.
hasLanguageOfToponym
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
C.
historicalLanguageOfBearers
Indicates that the specified language is historically spoken or used by the bearers of a given name, title, or designation.
-
D.
languageOfHistoricalRecord
Indicates the language in which a given historical record is written or recorded.
-
E.
regionHistoricalEthnonym
Indicates that a region is historically known or referred to by a particular ethnonym associated with a people or ethnic group.
- 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_69ee5bbd788481909e22bd7153d0c037 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 26, 2026, 7:12 p.m.