Triple
T8278446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lev Vygotsky |
E193605
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Orsha |
E215208
|
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: Orsha | Statement: [Lev Vygotsky, birthPlace, Orsha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orsha Context triple: [Lev Vygotsky, birthPlace, Orsha]
-
A.
Orsha
chosen
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
-
B.
Kozelsk
Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
-
C.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
D.
Vyazma
Vyazma is a historic town in Smolensk Oblast, western Russia, known for its strategic military significance, particularly during World War II.
-
E.
Pruzhany
Pruzhany is a historic town in western Belarus known for its cultural heritage and role as a local administrative and economic center.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ebb6b88190bc777b8bd72fcdbc |
completed | March 31, 2026, 7:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc6ca48308190bd7a6c84d5954279 |
completed | April 2, 2026, 1:30 a.m. |
Created at: March 30, 2026, 5:51 p.m.