Triple
T10443436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw suburban rail services |
E246224
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Legionowo |
E652755
|
NE 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: Legionowo | Statement: [Warsaw suburban rail services, connectsTo, Legionowo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Legionowo Context triple: [Warsaw suburban rail services, connectsTo, Legionowo]
-
A.
Legionowo
chosen
Legionowo is a commuter city in east-central Poland that functions as a suburban satellite of Warsaw within its metropolitan area.
-
B.
Piła
Piła is a city in northwestern Poland known as a regional economic and transport center in the Greater Poland Voivodeship.
-
C.
Strzelno
Strzelno is a town in north-central Poland best known as the birthplace of Nobel Prize–winning physicist Albert A. Michelson.
-
D.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
E.
Mrągowo
Mrągowo is a picturesque town in northeastern Poland known for its lakeside setting and popular summer cultural and music festivals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbd731c819084dfff83b4481ae8 |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ee0c2208190ae8d51a2a89a2586 |
completed | April 10, 2026, 4:38 a.m. |
Created at: April 6, 2026, 12:15 p.m.