Triple
T16697765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Istra |
E405759
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object | Voskresensk |
E138871
|
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: Voskresensk | Statement: [Istra, previousName, Voskresensk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Voskresensk Context triple: [Istra, previousName, Voskresensk]
-
A.
Voskresensk
chosen
Voskresensk is a town in Moscow Oblast, Russia, known for its industrial base and strong ice hockey tradition.
-
B.
Bogoroditsk
Bogoroditsk is a small historic town in western Russia known for its 18th-century palace-and-park ensemble and its role as a local industrial and cultural center.
-
C.
Bogorodskoye
Bogorodskoye is a rural locality in Russia that serves as one of the settlements within Nikolaevsky District.
-
D.
Bogorodskoye
Bogorodskoye is a rural locality in Russia that serves as the main administrative hub of Ulchsky District in Khabarovsk Krai.
-
E.
Bogorodsk
Bogorodsk is a historic Russian town that developed as a regional center of trade and crafts within the former Moscow Governorate.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3832e93c48190a594c498e9cc901a |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00919d02088190acecb1a62a100255 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.