Triple
T5961878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mari El |
E132656
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Yoshkar-Ola |
E271616
|
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: Yoshkar-Ola | Statement: [Mari El, largestCity, Yoshkar-Ola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoshkar-Ola Context triple: [Mari El, largestCity, Yoshkar-Ola]
-
A.
Yoshkar-Ola
chosen
Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
-
B.
Nukus
Nukus is the capital of the autonomous Republic of Karakalpakstan in western Uzbekistan, known for its remote desert location and the renowned Nukus Museum of Art.
-
C.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
D.
Kazanh
Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
-
E.
Kizlyar
Kizlyar is a town in the Republic of Dagestan, Russia, known historically as a frontier settlement and trading center in the North Caucasus region.
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c039ff421c819085fc92f0b707d31b |
completed | March 22, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3a5d54c8190b2bc8b3291f8ac2f |
completed | March 27, 2026, 1:55 a.m. |
Created at: March 22, 2026, 4:02 p.m.