Triple
T15684569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dukagjin region |
E380163
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Malisheva
Malisheva is a town and municipality in central Kosovo known for its location in the historical Dukagjin region and its role as a local administrative and economic center.
|
E1172294
|
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: Malisheva | Statement: [Dukagjin region, hasCity, Malisheva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malisheva Context triple: [Dukagjin region, hasCity, Malisheva]
-
A.
Govardeyskaya
Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
-
B.
Shkrebneva
Shkrebneva is the maiden surname of Lyudmila Putina, the former wife of Russian president Vladimir Putin.
-
C.
Skhodnenskaya
Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
-
D.
Grushevskaya
Grushevskaya is a Russian-language surname of Slavic origin.
-
E.
Korcheva
Korcheva was a historical town in the Tver region of Russia that served as an administrative center before being submerged by the Ivankovo Reservoir in the 1930s.
- 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: Malisheva Triple: [Dukagjin region, hasCity, Malisheva]
Generated description
Malisheva is a town and municipality in central Kosovo known for its location in the historical Dukagjin region and its role as a local administrative and economic center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Malisheva Target entity description: Malisheva is a town and municipality in central Kosovo known for its location in the historical Dukagjin region and its role as a local administrative and economic center.
-
A.
Govardeyskaya
Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
-
B.
Shkrebneva
Shkrebneva is the maiden surname of Lyudmila Putina, the former wife of Russian president Vladimir Putin.
-
C.
Skhodnenskaya
Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
-
D.
Grushevskaya
Grushevskaya is a Russian-language surname of Slavic origin.
-
E.
Korcheva
Korcheva was a historical town in the Tver region of Russia that served as an administrative center before being submerged by the Ivankovo Reservoir in the 1930s.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f31b5b881908e46ecd9fc6048ab |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff756ffcc88190a72440c7b40711ff |
completed | May 9, 2026, 5:57 p.m. |
| NEDg | Description generation | batch_69ff75e206a88190aace1904746d061f |
completed | May 9, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff765731bc819089c87cfb36628b01 |
completed | May 9, 2026, 6 p.m. |
Created at: April 10, 2026, 4:44 a.m.