Triple
T17452802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breslau Hauptbahnhof |
E424954
|
entity |
| Predicate | presentDayLanguageOfName |
P24399
|
FINISHED |
| Object | Polish |
—
|
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: Polish | Statement: [Breslau Hauptbahnhof, presentDayLanguageOfName, Polish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presentDayLanguageOfName Context triple: [Breslau Hauptbahnhof, presentDayLanguageOfName, Polish]
-
A.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
B.
hasDemonymLanguage
Indicates that a language is used as the demonym (people’s name or adjective of nationality) for inhabitants of a particular place or group.
-
C.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
D.
primaryUnitNameLanguage
Indicates the language in which the primary unit name is expressed or defined.
-
E.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4513faa0c8190961cf504c459bf34 |
completed | April 19, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f0e3fc819094e466b74622c956 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:47 a.m.