Triple
T19792135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamionka |
E475437
|
entity |
| Predicate | hasNeighbouringUnit |
P137347
|
FINISHED |
| Object | other districts of Mikołów |
—
|
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: other districts of Mikołów | Statement: [Kamionka, hasNeighbouringUnit, other districts of Mikołów]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbouringUnit Context triple: [Kamionka, hasNeighbouringUnit, other districts of Mikołów]
-
A.
hasNeighbouringQuarter
Indicates that one quarter (district or area) is directly adjacent to and shares a boundary with another quarter.
-
B.
hasNeighboringSite
Indicates that one site is located adjacent to or directly next to another site.
-
C.
hasNeighboringZone
Indicates that one zone is directly adjacent to or shares a boundary with another zone.
-
D.
hasNeighbouringLocality
Indicates that one locality is geographically adjacent to or directly borders another locality.
-
E.
hasNeighboringObject
Indicates that one object is located adjacent to or directly next to another object in space.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c37a3c819080f195d58adaaa7b |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:49 p.m.