Triple
T15793562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow State University main building |
E382917
|
entity |
| Predicate | wasTallestBuildingInEurope |
P2471
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 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: yes | Statement: [Moscow State University main building, wasTallestBuildingInEurope, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasTallestBuildingInEurope Context triple: [Moscow State University main building, wasTallestBuildingInEurope, yes]
-
A.
wasTallestStructureIn
Indicates that one structure held the status of being the tallest within a specified place or during a specified time period.
-
B.
tallestBuildingIn
chosen
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
C.
wasTallestBuildingOfType
Indicates that a building held the status of being the tallest among all buildings of a specified type (e.g., category, function, or classification) during a given context or time period.
-
D.
MjøstårnetHeight
Indicates the measured vertical height of Mjøstårnet.
-
E.
formerTallestBuildingInTheWorld
Indicates that a building once held, but no longer holds, the record for being the tallest building in the world.
- F. None of above.
Provenance (3 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4da381c819086195e3d20591abf |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.