Triple
T2766708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arsk Cemetery |
E61355
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Kazan Urban Okrug |
E35521
|
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: Kazan Urban Okrug | Statement: [Arsk Cemetery, hasMunicipality, Kazan Urban Okrug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazan Urban Okrug Context triple: [Arsk Cemetery, hasMunicipality, Kazan Urban Okrug]
-
A.
Kazan
chosen
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
-
B.
Krasnogorsk Urban Okrug
Krasnogorsk Urban Okrug is a municipal formation in Moscow Oblast, Russia, centered around the city of Krasnogorsk and forming part of the greater Moscow metropolitan area.
-
C.
Kirovsk
Kirovsk is an industrial town in Russia’s Murmansk Oblast, known for its mining industry and location in the Khibiny Mountains on the Kola Peninsula.
-
D.
Kirovsk
Kirovsk is a small industrial town in northwestern Russia, situated near Saint Petersburg along the Neva River.
-
E.
Krasnoselsky District
Krasnoselsky District is a central Moscow neighborhood known for its major transport hubs, historic architecture, and proximity to key administrative and cultural sites.
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd5762d08190a6286994a4e5dd92 |
completed | March 7, 2026, 8:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6496dc88190b316d5b36bc5df67 |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:57 p.m.