Triple
T26635440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlinchen |
E668621
|
entity |
| Predicate | nearbyLargerTown |
P42873
|
FINISHED |
| Object | Drawsko Pomorskie |
—
|
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: Drawsko Pomorskie | Statement: [Berlinchen, nearbyLargerTown, Drawsko Pomorskie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyLargerTown Context triple: [Berlinchen, nearbyLargerTown, Drawsko Pomorskie]
-
A.
nearestMajorTowns
Indicates that one or more major towns are the closest significant urban centers to a given location or entity.
-
B.
hasNearestLargerSettlement
chosen
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
C.
largestNearbyCity
Indicates that one city is the largest (by population, area, or another defined metric) among the cities located within a specified nearby region of another place or city.
-
D.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
E.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 2:27 a.m.