Triple
T10065728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luhansk Oblast |
E213097
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Krasnyi Luch
Krasnyi Luch is an industrial city in eastern Ukraine known for its coal mining and heavy industry.
|
E838882
|
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: Krasnyi Luch | Statement: [Luhansk Oblast, containsCity, Krasnyi Luch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krasnyi Luch Context triple: [Luhansk Oblast, containsCity, Krasnyi Luch]
-
A.
Sokol Kiev
Sokol Kiev was an ice hockey club from Kyiv that competed at the top level of Soviet hockey in the Soviet Championship League.
-
B.
Dmitrovskaya
Dmitrovskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the northern part of the city.
-
C.
Vityaz Podolsk
Vityaz Podolsk is a professional ice hockey club based in Podolsk, Russia, known for competing in the Kontinental Hockey League (KHL).
-
D.
Sokolka
Sokolka is a town in present-day northeastern Poland, historically part of the Grodno region, known for its multicultural heritage and role as a local administrative and trade center.
-
E.
Krasnov
Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
- 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: Krasnyi Luch Triple: [Luhansk Oblast, containsCity, Krasnyi Luch]
Generated description
Krasnyi Luch is an industrial city in eastern Ukraine known for its coal mining and heavy industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Krasnyi Luch Target entity description: Krasnyi Luch is an industrial city in eastern Ukraine known for its coal mining and heavy industry.
-
A.
Sokol Kiev
Sokol Kiev was an ice hockey club from Kyiv that competed at the top level of Soviet hockey in the Soviet Championship League.
-
B.
Dmitrovskaya
Dmitrovskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the northern part of the city.
-
C.
Vityaz Podolsk
Vityaz Podolsk is a professional ice hockey club based in Podolsk, Russia, known for competing in the Kontinental Hockey League (KHL).
-
D.
Sokolka
Sokolka is a town in present-day northeastern Poland, historically part of the Grodno region, known for its multicultural heritage and role as a local administrative and trade center.
-
E.
Krasnov
Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff51b108190b6759f651d4ba2d2 |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29a84c3308190ba9286053c1017dc |
completed | April 5, 2026, 5:23 p.m. |
| NEDg | Description generation | batch_69d29b985e308190a6ec3966e02f429c |
completed | April 5, 2026, 5:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d29c5f64c881909aa3d093422fe475 |
completed | April 5, 2026, 5:31 p.m. |
Created at: March 30, 2026, 8:58 p.m.