Triple
T22681576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotel Moskva |
E560494
|
entity |
| Predicate | wasNationalized |
P6034
|
FINISHED |
| Object | after World War II |
—
|
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: after World War II | Statement: [Hotel Moskva, wasNationalized, after World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasNationalized Context triple: [Hotel Moskva, wasNationalized, after World War II]
-
A.
nationalisedOn
Indicates the date or point in time when an entity was taken into state ownership or control by a national government.
-
B.
nationalised
chosen
Indicates that control or ownership of an entity has been transferred from private or non-state hands to the government or state.
-
C.
nationalisationYear
Indicates the year in which an entity was taken into state ownership or control through nationalisation.
-
D.
nationalizationReason
Indicates the reason or justification for which an entity is nationalized by a state or government.
-
E.
reasonForNationalization
Indicates the underlying cause or justification for which an entity was nationalized by a state.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1786027648190972d1b0bbe81ed13 |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:12 p.m.