Triple
T2775055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samara Oblast |
E61547
|
entity |
| Predicate | hasPortCity |
P2745
|
FINISHED |
| Object | Syzran |
E316657
|
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: Syzran | Statement: [Samara Oblast, hasPortCity, Syzran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Syzran Context triple: [Samara Oblast, hasPortCity, Syzran]
-
A.
Syzran
chosen
Syzran is a historic industrial city on the Volga River in western Russia, known for its oil refining, engineering industries, and regional transport significance.
-
B.
Kamyshin
Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
-
C.
Otradnoye
Otradnoye is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Otradnoye District in northern Moscow.
-
D.
Tikhvin
Tikhvin is a historic town in northwestern Russia known for its ancient monastery, religious icons, and role as a regional cultural and industrial center.
-
E.
Volzhsky
Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd7f9570819087f1b1cb59d68586 |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12dfe893c81909c79ea6cffb5bae6 |
completed | March 11, 2026, 8:55 a.m. |
Created at: March 6, 2026, 9:57 p.m.