Triple
T30773750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prospekt Lenina |
E783601
|
entity |
| Predicate | typicalType |
P76740
|
FINISHED |
| Object | avenue |
—
|
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: avenue | Statement: [Prospekt Lenina, typicalType, avenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalType Context triple: [Prospekt Lenina, typicalType, avenue]
-
A.
typicalConformingType
Indicates that one entity is a standard or representative instance that conforms to the defining characteristics or constraints of another entity’s type.
-
B.
typicalCoreType
Indicates that something is a standard or characteristic core type within a given classification or system.
-
C.
typicalTargetType
Indicates the usual or most common type or category of entity that serves as the target or recipient in a given relationship or action.
-
D.
typicalEntryType
Indicates the usual or standard category or kind of entry associated with something.
-
E.
typicalObjectType
chosen
Indicates that something is a common or characteristic type of object typically associated with or involved in another entity or situation.
- 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_69f224b1519081908b9db003fd2073e0 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:40 p.m.