Triple
T8949241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belevsky Uyezd |
E213300
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Belev |
E768301
|
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: Belev | Statement: [Belevsky Uyezd, namedAfter, Belev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belev Context triple: [Belevsky Uyezd, namedAfter, Belev]
-
A.
Belev
chosen
Belev is a historic town in Tula Oblast, Russia, known for its medieval origins and role as a local administrative and cultural center.
-
B.
Balasinor
Balasinor is a town in Gujarat, India, known for its nearby dinosaur fossil park and rich paleontological significance.
-
C.
Berriane
Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
-
D.
Belsand
Belsand is a small town in the Sitamarhi district of the Indian state of Bihar, known primarily as a local administrative and market center for surrounding rural areas.
-
E.
Overath
Overath is a small town in western Germany’s North Rhine-Westphalia, situated near Cologne within the broader Rhine-Ruhr urban area.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670b5f50819080f1c73992fe5281 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc93c678c81909d2ab68308d7c2f0 |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 6:59 p.m.