Triple
T38351673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łęknica |
E1046200
|
entity |
| Predicate | nearbyGermanTown |
P199497
|
FINISHED |
| Object | Bad Muskau |
—
|
NE NERFINISHED |
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: Bad Muskau | Statement: [Łęknica, nearbyGermanTown, Bad Muskau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyGermanTown Context triple: [Łęknica, nearbyGermanTown, Bad Muskau]
-
A.
nearbySettlementGR
Indicates that one settlement is geographically located close to another settlement.
-
B.
federalStateCapitalNearby
Indicates that the capital city of a federal state is geographically close to a specified reference location or entity.
-
C.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
D.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
E.
nearestTownSerbia
Indicates the relationship where a given location is associated with the geographically closest town within the territory of Serbia.
- 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_69f76e3a94fc81908edc175e8d259e80 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff3e1762d8819089a60e402e682817 |
completed | May 9, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69ff3d8c6f308190a0646b1432752eb8 |
completed | May 9, 2026, 1:58 p.m. |
| PDg | Predicate description generation | batch_69ff3e16527c81908c8d89da704ce012 |
completed | May 9, 2026, 2 p.m. |
Created at: May 3, 2026, 4:31 p.m.