Triple
T1941476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ipswich |
E41563
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Gdansk |
E18213
|
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: Gdansk | Statement: [Ipswich, hasTwinTown, Gdansk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gdansk Context triple: [Ipswich, hasTwinTown, Gdansk]
-
A.
Gdańsk
chosen
Gdańsk is a major Polish port city on the Baltic Sea, known for its rich Hanseatic history, shipyards, and role in the origins of the Solidarity movement.
-
B.
Gdynia
Gdynia is a major seaport city on Poland’s Baltic coast, developed rapidly in the 20th century into one of the country’s key maritime and economic centers.
-
C.
Szczecin
Szczecin is a large Polish city and important maritime and industrial center in northwestern Poland, situated near the Baltic Sea and the German border.
-
D.
Sopot
Sopot is a suburban municipality of Belgrade, Serbia, known for its rural character and proximity to the Avala and Kosmaj mountains.
-
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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2fb21fc8190929ea4a87ef4402e |
completed | March 7, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc01252ec8190a14ff51151d8e69e |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 4, 2026, 7:36 p.m.