Triple
T9874899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perm Krai |
E240048
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Gubakha
Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
|
E826717
|
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: Gubakha | Statement: [Perm Krai, hasCity, Gubakha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gubakha Context triple: [Perm Krai, hasCity, Gubakha]
-
A.
Gubin
Gubin is a town in western Poland situated on the Lusatian Neisse River, directly opposite the German town of Guben, forming a cross-border urban area.
-
B.
Chorokhi
Chorokhi is a river in the South Caucasus that flows from northeastern Turkey into southwestern Georgia before emptying into the Black Sea.
-
C.
Goubuli
Goubuli is a famous Chinese food brand best known for its traditional Tianjin-style stuffed buns (baozi) with a long history and strong cultural recognition.
-
D.
Doboka
Doboka is a town in the Nagaon district of Assam, India, known as a local commercial and transportation hub for the surrounding rural areas.
-
E.
Chakvi
Chakvi is a small resort town on Georgia’s Black Sea coast, known for its subtropical climate, tea plantations, and proximity to Mtirala National Park.
- 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: Gubakha Triple: [Perm Krai, hasCity, Gubakha]
Generated description
Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gubakha Target entity description: Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
-
A.
Gubin
Gubin is a town in western Poland situated on the Lusatian Neisse River, directly opposite the German town of Guben, forming a cross-border urban area.
-
B.
Chorokhi
Chorokhi is a river in the South Caucasus that flows from northeastern Turkey into southwestern Georgia before emptying into the Black Sea.
-
C.
Goubuli
Goubuli is a famous Chinese food brand best known for its traditional Tianjin-style stuffed buns (baozi) with a long history and strong cultural recognition.
-
D.
Doboka
Doboka is a town in the Nagaon district of Assam, India, known as a local commercial and transportation hub for the surrounding rural areas.
-
E.
Chakvi
Chakvi is a small resort town on Georgia’s Black Sea coast, known for its subtropical climate, tea plantations, and proximity to Mtirala National Park.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f9d82c81908afb4977ce4e3e4a |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e47515788190b6644021e187e771 |
completed | April 5, 2026, 4:26 a.m. |
| NEDg | Description generation | batch_69d1e57366748190bf617374264d1873 |
completed | April 5, 2026, 4:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1e5ed9818819095119c3478f97419 |
completed | April 5, 2026, 4:32 a.m. |
Created at: March 30, 2026, 8:37 p.m.