Triple
T3630756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Poland |
E76947
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Łeba |
E294188
|
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: Łeba | Statement: [Northern Poland, includesCity, Łeba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Łeba Context triple: [Northern Poland, includesCity, Łeba]
-
A.
Łeba
chosen
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
B.
Mrągowo
Mrągowo is a picturesque town in northeastern Poland known for its lakeside setting and popular summer cultural and music festivals.
-
C.
Piła
Piła is a city in northwestern Poland known as a regional economic and transport center in the Greater Poland Voivodeship.
-
D.
Tczew
Tczew is a historic town in northern Poland on the Vistula River, known for its important railway bridges and role as a regional transport hub.
-
E.
Elbląg
Elbląg is a historic city in northern Poland known for its reconstructed Old Town, medieval heritage, and role as an important port and industrial center.
- 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30136e88190922bb542971b5239 |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfd2366a3c819097391ad8731c21a8 |
completed | March 22, 2026, 11:27 a.m. |
Created at: March 8, 2026, 3:23 p.m.