Triple
T323391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Metro |
E6462
|
entity |
| Predicate | signageLanguage |
P4196
|
FINISHED |
| Object | Russian |
—
|
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: Russian | Statement: [Moscow Metro, signageLanguage, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signageLanguage Context triple: [Moscow Metro, signageLanguage, Russian]
-
A.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
-
B.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
C.
emblemLanguage
Indicates that an emblem (such as a symbol or logo) is associated with or presented in a particular language.
-
D.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
E.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea82ba748190bae651f5de908617 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e948048c819098ba4de9261ef2ef |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.