Triple
T2919453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater Poland Voivodeship |
E78683
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Piła |
E341962
|
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: Piła | Statement: [Greater Poland Voivodeship, containsCity, Piła]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Piła Context triple: [Greater Poland Voivodeship, containsCity, Piła]
-
A.
Piła
chosen
Piła is a city in northwestern Poland known as a regional economic and transport center in the Greater Poland Voivodeship.
-
B.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
C.
Świnoujście
Świnoujście is a Polish port city and seaside resort on the Baltic Sea, known for its wide beaches, spa facilities, and strategic location at the mouth of the Świna River.
-
D.
Brzeg
Brzeg is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
-
E.
Sopot
Sopot is a Polish Baltic Sea resort city famous for its sandy beaches, long wooden pier, and vibrant spa and nightlife culture.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a53f8c8190b188d549f1161e84 |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe34c0908190a618ff01ee27bfbb |
completed | March 21, 2026, 8:23 p.m. |
Created at: March 8, 2026, 2:54 p.m.