Triple
T17295628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivanovo Oblast |
E419902
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kineshma
Kineshma is a historic town in central Russia situated on the Volga River, known as one of the larger urban centers of Ivanovo Oblast.
|
E1261619
|
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: Kineshma | Statement: [Ivanovo Oblast, contains, Kineshma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kineshma Context triple: [Ivanovo Oblast, contains, Kineshma]
-
A.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
-
B.
Klemtu
Klemtu is a small, remote First Nations community on Swindle Island along British Columbia’s Inside Passage, known for its rich Kitasoo/Xai’xais culture and access to the Great Bear Rainforest.
-
C.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
-
D.
Olenka
Olenka is a Slavic diminutive form of the female given name Olga, often used as an affectionate or familiar nickname.
-
E.
Kagermeer
Kagermeer is a lake in the Kagerplassen lake district in South Holland, Netherlands, popular for boating and watersports.
- 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: Kineshma Triple: [Ivanovo Oblast, contains, Kineshma]
Generated description
Kineshma is a historic town in central Russia situated on the Volga River, known as one of the larger urban centers of Ivanovo Oblast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kineshma Target entity description: Kineshma is a historic town in central Russia situated on the Volga River, known as one of the larger urban centers of Ivanovo Oblast.
-
A.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
-
B.
Klemtu
Klemtu is a small, remote First Nations community on Swindle Island along British Columbia’s Inside Passage, known for its rich Kitasoo/Xai’xais culture and access to the Great Bear Rainforest.
-
C.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
-
D.
Olenka
Olenka is a Slavic diminutive form of the female given name Olga, often used as an affectionate or familiar nickname.
-
E.
Kagermeer
Kagermeer is a lake in the Kagerplassen lake district in South Holland, Netherlands, popular for boating and watersports.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437875b208190bcf0df2ded546257 |
completed | April 19, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180d66bb8819086eb2c72b4dcbafb |
completed | May 11, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_6a01848c84cc8190bbcf1a8be82d0f68 |
completed | May 11, 2026, 7:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01850519108190972c1ecea6b9313c |
completed | May 11, 2026, 7:28 a.m. |
Created at: April 10, 2026, 5:40 a.m.