Triple
T24339561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergmannkiez |
E613474
|
entity |
| Predicate | belongsToCityState |
P155770
|
FINISHED |
| Object | state of Berlin |
—
|
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: state of Berlin | Statement: [Bergmannkiez, belongsToCityState, state of Berlin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToCityState Context triple: [Bergmannkiez, belongsToCityState, state of Berlin]
-
A.
containsCityState
Indicates that one entity includes or encompasses a specific city and state within its scope or boundaries.
-
B.
associatedCityState
Indicates a relationship where a city is linked to the state with which it is formally or contextually connected.
-
C.
basedInCityState
Indicates that an entity’s primary location or headquarters is situated in a specific city within a specific state.
-
D.
belongsToCityType
Indicates that one entity is classified under, or associated with, a particular type or category of city.
-
E.
belongsToNationState
Indicates that an entity is a member, part, or constituent of a specific nation-state, reflecting a formal or recognized association with that country.
- F. None of above. chosen
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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932324e8819082344cf42eddc274 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28b7ff1808190870dfe9af789a1eb |
completed | April 29, 2026, 10:51 p.m. |
Created at: April 18, 2026, 1:57 a.m.