Triple
T8833224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgas Province |
E210197
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kameno
Kameno is a small town and municipality in southeastern Bulgaria known for its agricultural surroundings and proximity to the regional center of Burgas.
|
E759999
|
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: Kameno | Statement: [Burgas Province, contains, Kameno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kameno Context triple: [Burgas Province, contains, Kameno]
-
A.
Zakopianka
Zakopianka is a major Polish road corridor connecting Kraków with the mountain resort town of Zakopane, serving as a primary route to the Tatra Mountains.
-
B.
Karpenisi
Karpenisi is a small mountainous town in central Greece known for its scenic landscapes, winter sports, and traditional Greek character.
-
C.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
D.
Koropi
Koropi is a town in the Athens metropolitan area of Greece, known as the seat of the municipality of Kropia and a local hub in the Mesogeia plain.
-
E.
Vidnoye
Vidnoye is a small town in Moscow Oblast, Russia, functioning largely as a residential and industrial satellite 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: Kameno Triple: [Burgas Province, contains, Kameno]
Generated description
Kameno is a small town and municipality in southeastern Bulgaria known for its agricultural surroundings and proximity to the regional center of Burgas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kameno Target entity description: Kameno is a small town and municipality in southeastern Bulgaria known for its agricultural surroundings and proximity to the regional center of Burgas.
-
A.
Zakopianka
Zakopianka is a major Polish road corridor connecting Kraków with the mountain resort town of Zakopane, serving as a primary route to the Tatra Mountains.
-
B.
Karpenisi
Karpenisi is a small mountainous town in central Greece known for its scenic landscapes, winter sports, and traditional Greek character.
-
C.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
D.
Koropi
Koropi is a town in the Athens metropolitan area of Greece, known as the seat of the municipality of Kropia and a local hub in the Mesogeia plain.
-
E.
Vidnoye
Vidnoye is a small town in Moscow Oblast, Russia, functioning largely as a residential and industrial satellite 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60670fa48190b2a873f6498de7f6 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf8975a6f481908ee435d0435c8ffb |
completed | April 3, 2026, 9:33 a.m. |
| NEDg | Description generation | batch_69cf8a8e5db0819080e6fdc3d8322e94 |
completed | April 3, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf8b8849ec8190915fa087b1b46c18 |
completed | April 3, 2026, 9:42 a.m. |
Created at: March 30, 2026, 6:47 p.m.