Triple
T38413966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dresden dialect |
E901553
|
entity |
| Predicate | typicalOfCity |
P136309
|
FINISHED |
| Object | Dresden |
E37454
|
NE 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: Dresden | Statement: [Dresden dialect, typicalOfCity, Dresden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOfCity Context triple: [Dresden dialect, typicalOfCity, Dresden]
-
A.
typicalCityExample
Indicates that the subject is a representative or characteristic example of a city, illustrating typical features or qualities associated with cities.
-
B.
usualCity
chosen
Indicates that a city is the standard, typical, or commonly associated city for a given entity (such as a person, organization, or activity).
-
C.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
D.
concentratedInCity
Indicates that a large proportion or primary presence of something is located within a particular city.
-
E.
typicalVenueCity
Indicates that a particular city is the usual or standard location where an event, activity, or organization is typically held or based.
- F. None of above.
Provenance (4 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a42458f9b488190bcb5eda521b43707 |
completed | June 29, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.