Triple
T3595708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rzhev–Vyazma strategic operations |
E76134
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Vyazma |
E366953
|
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: Vyazma | Statement: [Rzhev–Vyazma strategic operations, near, Vyazma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vyazma Context triple: [Rzhev–Vyazma strategic operations, near, Vyazma]
-
A.
Vyazma
chosen
Vyazma is a historic town in Smolensk Oblast, western Russia, known for its strategic military significance, particularly during World War II.
-
B.
Rzhev
Rzhev is a historic town in western Russia known for its strategic location on the Volga River and as the site of major World War II battles.
-
C.
Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
-
D.
Yudenich
Yudenich is a Russian surname most notably associated with General Nikolai Yudenich, a leading White movement commander during the Russian Civil War.
-
E.
Orsha
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc15f41cc819085b3e897d823757d |
completed | March 8, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4882803e481908bc716c8beda3c73 |
completed | March 13, 2026, 9:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.