Triple
T34670632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Station Square |
E890368
|
entity |
| Predicate | hasRussianNickname |
P20560
|
FINISHED |
| Object | Площадь трёх вокзалов |
—
|
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: Площадь трёх вокзалов | Statement: [Three Station Square, hasRussianNickname, Площадь трёх вокзалов]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRussianNickname Context triple: [Three Station Square, hasRussianNickname, Площадь трёх вокзалов]
-
A.
nameInRussian
chosen
Indicates that an entity is known or referred to by a specific name when expressed in the Russian language.
-
B.
hasNicknames
Indicates that an entity is known or referred to by one or more alternative informal names.
-
C.
isOfficialNicknameOf
Indicates that one name is the formally recognized nickname or informal moniker used to refer to another entity.
-
D.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
E.
unofficialNickname
Indicates that one entity is informally or colloquially known by a non-official nickname represented by the other entity.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: May 1, 2026, 2:05 a.m.