Triple
T1890140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dnieper |
E41855
|
entity |
| Predicate | passesThroughCity |
P416
|
FINISHED |
| Object |
Orsha
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
|
E215208
|
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: Orsha | Statement: [Dnieper, passesThroughCity, Orsha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orsha Context triple: [Dnieper, passesThroughCity, Orsha]
-
A.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
B.
Lichtenrade
Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
-
C.
Włodawa
Włodawa is a town in eastern Poland near the borders with Belarus and Ukraine, known for its multicultural heritage and proximity to the former Sobibor extermination camp.
-
D.
Smolensk
Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
-
E.
Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
- 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: Orsha Triple: [Dnieper, passesThroughCity, Orsha]
Generated description
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orsha Target entity description: Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
-
A.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
B.
Lichtenrade
Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
-
C.
Włodawa
Włodawa is a town in eastern Poland near the borders with Belarus and Ukraine, known for its multicultural heritage and proximity to the former Sobibor extermination camp.
-
D.
Smolensk
Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
-
E.
Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb14475448190b291ada3454bf98b |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3cc8d5c8190bee638183989830c |
completed | March 8, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69adf48412b08190b6ad0f3abf42a081 |
completed | March 8, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf4f7c908819089ccdc881af10da9 |
completed | March 8, 2026, 10:15 p.m. |
Created at: March 4, 2026, 7:34 p.m.