Triple
T17546639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akazienstraße |
E427341
|
entity |
| Predicate | hasCaféCulture |
P82187
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Akazienstraße, hasCaféCulture, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaféCulture Context triple: [Akazienstraße, hasCaféCulture, yes]
-
A.
hasCoffeeCulture
chosen
Indicates that a place or group is characterized by established social practices, traditions, and norms centered around the consumption and appreciation of coffee.
-
B.
hasCafes
Indicates that one entity possesses, contains, or includes one or more cafes within it.
-
C.
hasLoungeOrCafe
Indicates that one entity provides or includes access to a lounge or café associated with another entity.
-
D.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
-
E.
hasRestaurantsAndCafes
Indicates that the subject location contains or provides access to restaurants and cafés.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454626cfc8190a2602ba4934b8e6d |
completed | April 19, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.