Triple
T48846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hero of Socialist Labour |
E959
|
entity |
| Predicate | officialNameInRussian |
P657
|
FINISHED |
| Object | Герой Социалистического Труда |
—
|
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: Герой Социалистического Труда | Statement: [Hero of Socialist Labour, officialNameInRussian, Герой Социалистического Труда]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialNameInRussian Context triple: [Hero of Socialist Labour, officialNameInRussian, Герой Социалистического Труда]
-
A.
officialName
Indicates the formally recognized name assigned to an entity by an authoritative body or source.
-
B.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
C.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
D.
nativeLabel
chosen
Indicates the label or name of an entity expressed in its own native or original language.
-
E.
nameOf
Indicates that one entity is the name or designation of another 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c1a5c14819088748317a3f262c8 |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24abfa7bc8190932c137a823efcb6 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.