Triple
T4015306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayerisches Viertel |
E90741
|
entity |
| Predicate | streetNamingTheme |
P36245
|
FINISHED |
| Object | Bavarian towns and regions |
—
|
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: Bavarian towns and regions | Statement: [Bayerisches Viertel, streetNamingTheme, Bavarian towns and regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetNamingTheme Context triple: [Bayerisches Viertel, streetNamingTheme, Bavarian towns and regions]
-
A.
hasStreetNamingPattern
chosen
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
B.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
-
C.
streetOrAreaType
Indicates the specific kind or classification of a street or area (such as avenue, boulevard, district, or zone) associated with an entity.
-
D.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
E.
squareName
Indicates that an entity is identified by or associated with the name of a square (such as a public square or plaza).
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:35 p.m.