Triple

T32718832
Position Surface form Disambiguated ID Type / Status
Subject Taganskaya E836605 entity
Predicate hasSignageScript P47313 FINISHED
Object Cyrillic 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: Cyrillic | Statement: [Taganskaya, hasSignageScript, Cyrillic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSignageScript
Context triple: [Taganskaya, hasSignageScript, Cyrillic]
  • A. hasSignage
    Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
  • B. scriptUsedInSignage chosen
    Indicates that a particular writing system or script is employed in the text or graphics of a sign or signage.
  • C. hasSignageIn
    Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
  • D. hasSignageType
    Indicates the specific category or kind of signage associated with an object, location, or entity.
  • E. hasSignageLetter
    Indicates that an object or location bears signage containing a specific letter or set of letters.
  • 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_69f34935455881909088975d79460418 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fd2cf39b0c8190811b8a6fa9410560 completed May 8, 2026, 12:23 a.m.
PD Predicate disambiguation batch_69fd2ad8dd988190a9899701ba00d917 completed May 8, 2026, 12:14 a.m.
Created at: May 1, 2026, 1:11 a.m.