Triple
T19807356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syas River |
E475847
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Lodeynoye Pole |
—
|
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: Lodeynoye Pole | Statement: [Syas River, hasNearbySettlement, Lodeynoye Pole]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lodeynoye Pole Context triple: [Syas River, hasNearbySettlement, Lodeynoye Pole]
-
A.
Lodeynoye Pole
chosen
Lodeynoye Pole is a small town in northwestern Russia known as an administrative center and river port in the Leningrad (Saint Petersburg) region.
-
B.
Lomonosovo
Lomonosovo is a rural locality in Russia’s Arkhangelsk Oblast, best known as the birthplace of the polymath Mikhail Lomonosov.
-
C.
Wrangel
Wrangel is a Baltic German noble family name most famously associated with Pyotr Wrangel, a prominent White Army commander during the Russian Civil War.
-
D.
Wrangelkiez
Wrangelkiez is a lively, densely populated neighborhood in Berlin’s Kreuzberg district, known for its multicultural atmosphere, street art, bars, and proximity to the River Spree.
-
E.
Ostrov
Ostrov is a historic town in Pskov Oblast, Russia, known for its medieval architecture and role as a regional administrative 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.