Triple
T4194921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sura River |
E89123
|
entity |
| Predicate | hasCityOnBank |
P7935
|
FINISHED |
| Object | Penza |
E276204
|
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: Penza | Statement: [Sura River, hasCityOnBank, Penza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penza Context triple: [Sura River, hasCityOnBank, Penza]
-
A.
Penza
chosen
Penza is a city in western Russia known as a regional cultural and industrial center.
-
B.
Izhevsk
Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
-
C.
Tambov
Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
-
D.
Ulyanovsk
Ulyanovsk is a city in western Russia on the Volga River, best known as the birthplace of Vladimir Lenin and an important regional industrial and cultural center.
-
E.
Voronezh
Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af034406348190a56c21b5c08a6828 |
completed | March 9, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfbd56f4c081909ebc19bfc91aa5d2 |
completed | March 22, 2026, 9:58 a.m. |
Created at: March 9, 2026, 3:46 p.m.