Triple
T20681577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svetlana Khorkina |
E508304
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Belgorod |
—
|
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: Belgorod | Statement: [Svetlana Khorkina, placeOfBirth, Belgorod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belgorod Context triple: [Svetlana Khorkina, placeOfBirth, Belgorod]
-
A.
Belgorod
chosen
Belgorod is a city in western Russia near the Ukrainian border, historically significant as a strategic site of major World War II battles and offensives.
-
B.
Voronezh
Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
-
C.
Oryol
Oryol is a historic city in western Russia situated on the Oka River, known as a regional cultural and administrative center.
-
D.
Oryol
Oryol was a notable warship of the Imperial Russian Navy, recognized for its role in Russia’s early modern naval history.
-
E.
Tambov
Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea842dc81908106a0c29d1577aa |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 11:45 a.m.