Triple
T16867228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curzon Line |
E410072
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Białystok |
—
|
NE NERFINISHED |
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: Białystok | Statement: [Curzon Line, passesNear, Białystok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Białystok Context triple: [Curzon Line, passesNear, Białystok]
-
A.
Białystok
chosen
Białystok is a city in northeastern Poland best known as the birthplace of L. L. Zamenhof and the cradle of the international language Esperanto.
-
B.
Bydgoszcz
Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
-
C.
Olsztyn
Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of the Warmian-Masurian Voivodeship.
-
D.
Lublin
Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
-
E.
Radom
Radom is a city in central Poland known as an important regional industrial and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b50983148190a116f7e7017ccb1c |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:24 a.m.