Triple
T15636986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | trolleybus line 21 (Gdynia–Sopot) |
E375970
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Sopot |
E77811
|
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: Sopot | Statement: [trolleybus line 21 (Gdynia–Sopot), terminus, Sopot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sopot Context triple: [trolleybus line 21 (Gdynia–Sopot), terminus, Sopot]
-
A.
Sopot
chosen
Sopot is a Polish Baltic Sea resort city famous for its sandy beaches, long wooden pier, and vibrant spa and nightlife culture.
-
B.
Sopot
Sopot is a suburban municipality of Belgrade, Serbia, known for its rural character and proximity to the Avala and Kosmaj mountains.
-
C.
Serock
Serock is a locality situated near the Western Bug River in eastern Europe.
-
D.
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.
-
E.
Bydgoszcz
Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eba51f08190ac5d9de7fc89405a |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0167369d9481909015c34d475fac14 |
completed | May 11, 2026, 5:20 a.m. |
Created at: April 10, 2026, 4:14 a.m.