Triple
T1879317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donbas |
E39814
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Kramatorsk
Kramatorsk is an industrial city in eastern Ukraine that has become a key administrative and strategic center in the Donbas region.
|
E261065
|
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: Kramatorsk | Statement: [Donbas, hasCity, Kramatorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kramatorsk Context triple: [Donbas, hasCity, Kramatorsk]
-
A.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
B.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
C.
Mariupol
Mariupol is a major industrial city in southeastern Ukraine known for its strategic port on the Sea of Azov and its significant role in recent military conflicts.
-
D.
Horlivka
Horlivka is an industrial city in eastern Ukraine’s Donetsk region, known for its coal mining and chemical industries and its location within the contested Donbas area.
-
E.
Donetsk
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
- 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: Kramatorsk Triple: [Donbas, hasCity, Kramatorsk]
Generated description
Kramatorsk is an industrial city in eastern Ukraine that has become a key administrative and strategic center in the Donbas region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kramatorsk Target entity description: Kramatorsk is an industrial city in eastern Ukraine that has become a key administrative and strategic center in the Donbas region.
-
A.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
B.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
C.
Mariupol
Mariupol is a major industrial city in southeastern Ukraine known for its strategic port on the Sea of Azov and its significant role in recent military conflicts.
-
D.
Horlivka
Horlivka is an industrial city in eastern Ukraine’s Donetsk region, known for its coal mining and chemical industries and its location within the contested Donbas area.
-
E.
Donetsk
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f8e9f08190a210440823fad69e |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea8405a58819096dc1eeea8fc0b93 |
completed | March 9, 2026, 11 a.m. |
| NEDg | Description generation | batch_69aeac2435e88190ae38a1a4d20c4872 |
completed | March 9, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeaca11b008190b34397bdf7aa0669 |
completed | March 9, 2026, 11:18 a.m. |
Created at: March 4, 2026, 7:34 p.m.