Triple
T10083042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Principality of Yaroslavl |
E213948
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object |
Zalesye
Zalesye is a historic region in northeastern European Russia that served as an early center of medieval Rus’ settlement and state formation.
|
E841402
|
NE FINISHED |
How this triple was built (4 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: Zalesye | Statement: [Principality of Yaroslavl, historicalRegion, Zalesye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zalesye Context triple: [Principality of Yaroslavl, historicalRegion, Zalesye]
-
A.
Zolotonosha
Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
-
B.
Zaosie
Zaosie is a small village in present-day Belarus, best known as the birthplace of the Polish Romantic poet Adam Mickiewicz.
-
C.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
D.
Bronnitsy
Bronnitsy is a historic town in Russia known for its jewelry-making traditions and its location southeast of Moscow along the Moskva River.
-
E.
Zhulebino
Zhulebino is a station on the Moscow Metro system, serving the residential Zhulebino district in the southeastern part of Moscow.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zalesye Triple: [Principality of Yaroslavl, historicalRegion, Zalesye]
Generated description
Zalesye is a historic region in northeastern European Russia that served as an early center of medieval Rus’ settlement and state formation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zalesye Target entity description: Zalesye is a historic region in northeastern European Russia that served as an early center of medieval Rus’ settlement and state formation.
-
A.
Zolotonosha
Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
-
B.
Zaosie
Zaosie is a small village in present-day Belarus, best known as the birthplace of the Polish Romantic poet Adam Mickiewicz.
-
C.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
D.
Bronnitsy
Bronnitsy is a historic town in Russia known for its jewelry-making traditions and its location southeast of Moscow along the Moskva River.
-
E.
Zhulebino
Zhulebino is a station on the Moscow Metro system, serving the residential Zhulebino district in the southeastern part of Moscow.
- F. None of above. chosen
Provenance (5 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04352d081908f676444cd2d2578 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b675f4b08190bd8285f210191b93 |
completed | April 5, 2026, 7:22 p.m. |
| NEDg | Description generation | batch_69d2ba645ec08190b33388a40ca7582e |
completed | April 5, 2026, 7:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2babd01908190b5c9f9c3541361ee |
completed | April 5, 2026, 7:40 p.m. |
Created at: March 30, 2026, 9 p.m.