Triple
T3822803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hel Peninsula railway line |
E88614
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Chałupy |
E90311
|
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: Chałupy | Statement: [Hel Peninsula railway line, passesThrough, Chałupy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chałupy Context triple: [Hel Peninsula railway line, passesThrough, Chałupy]
-
A.
Chałupy
chosen
Chałupy is a small Polish seaside village and popular windsurfing and kitesurfing spot on the Baltic coast.
-
B.
Szaflary
Szaflary is a village in southern Poland’s Podhale region, known for its geothermal hot springs and traditional highland culture.
-
C.
Sukiennice
Sukiennice is a historic Renaissance cloth hall and landmark market building located in the main square of Kraków, Poland.
-
D.
Krzywy Domek
Krzywy Domek is a famously surreal, crooked-shaped building in Sopot, Poland, known for its whimsical, fairy-tale architecture and role as a popular tourist attraction.
-
E.
Sokółka
Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeea63fe2c8190825f6e9451f6aa50 |
completed | March 9, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb4c70008190bb8712f46f40d6f8 |
completed | March 14, 2026, 6:08 a.m. |
Created at: March 9, 2026, 3:17 p.m.