Triple
T1273881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakheti |
E15768
|
entity |
| Predicate | hasWineAppellation |
P6176
|
FINISHED |
| Object |
Mukuzani
Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
|
E151809
|
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: Mukuzani | Statement: [Kakheti, hasWineAppellation, Mukuzani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mukuzani Context triple: [Kakheti, hasWineAppellation, Mukuzani]
-
A.
Mtiuleti
Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
-
B.
Murambi
Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
-
C.
Mafadi
Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
-
D.
Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
-
E.
Tuka
Tuka is the affectionate self-referential name used by the 17th-century Marathi saint-poet Tukaram in his devotional abhangas.
- 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: Mukuzani Triple: [Kakheti, hasWineAppellation, Mukuzani]
Generated description
Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mukuzani Target entity description: Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
-
A.
Mtiuleti
Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
-
B.
Murambi
Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
-
C.
Mafadi
Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
-
D.
Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
-
E.
Tuka
Tuka is the affectionate self-referential name used by the 17th-century Marathi saint-poet Tukaram in his devotional abhangas.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c48bec548190b25d4a74b323cc1b |
completed | March 1, 2026, 10:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf1fa1148190a8a8a5b3e34946f0 |
completed | March 8, 2026, 12:13 a.m. |
| NEDg | Description generation | batch_69acbf873544819099d3dff98a6b2244 |
completed | March 8, 2026, 12:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc06483b08190b5b29f684b83f43f |
completed | March 8, 2026, 12:18 a.m. |
Created at: March 1, 2026, 7:50 p.m.