Triple
T13207697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarapul |
E314407
|
entity |
| Predicate | locatedSoutheastOf |
P5143
|
FINISHED |
| Object | Izhevsk |
E526368
|
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: Izhevsk | Statement: [Sarapul, locatedSoutheastOf, Izhevsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Izhevsk Context triple: [Sarapul, locatedSoutheastOf, Izhevsk]
-
A.
Izhevsk
chosen
Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
-
B.
Simbirsk
Simbirsk is a historic Russian city on the Volga River, best known today as Ulyanovsk, the birthplace of Vladimir Lenin and other notable political figures.
-
C.
Penza
Penza is a city in western Russia known as a regional cultural and industrial center.
-
D.
Lipetsk
Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
-
E.
Tolyatti
Tolyatti is a major industrial city in Russia on the Volga River, best known as the home of the AvtoVAZ automobile plant that produces Lada cars.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9cb7ac819095cff8699993c419 |
completed | April 10, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde15abe6c8190a6212861bbce790e |
completed | May 8, 2026, 1:12 p.m. |
Created at: April 9, 2026, 9:17 p.m.