Triple
T17948563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Petersburg suburban railways |
E448767
|
entity |
| Predicate | connectsToTown |
P60933
|
FINISHED |
| Object | Kingisepp |
—
|
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: Kingisepp | Statement: [Saint Petersburg suburban railways, connectsToTown, Kingisepp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kingisepp Context triple: [Saint Petersburg suburban railways, connectsToTown, Kingisepp]
-
A.
Kingisepp
chosen
Kingisepp is a town in northwestern Russia near the Estonian border, known for its industrial base and historical roots dating back to the 14th century.
-
B.
Makov
Makov is a Slovak village and popular mountain resort known as a key gateway for hiking and winter sports in the Javorníky Mountains.
-
C.
Muroran
Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
-
D.
Zikhron Ya’akov
Zikhron Ya’akov is a historic town in northern Israel known for its early Zionist agricultural settlement, wineries, and scenic location overlooking the Mediterranean.
-
E.
Lichtenrade
Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afaac780819097434b20b1f155d2 |
completed | April 19, 2026, 10:34 a.m. |
Created at: April 10, 2026, 10:21 a.m.