Triple

T32908485

Position	Surface form	Disambiguated ID	Type / Status
Subject	Rovno	`E841806`	entity
Predicate	standardizedNameInUkrainian	`P25447`	FINISHED
Object	Рівне Рівне is a city in western Ukraine that serves as the administrative center of Rivne Oblast and an important regional economic and cultural hub.	`E2027615`	NE FINISHED

How this triple was built (3 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: Рівне | Statement: [Rovno, standardizedNameInUkrainian, Рівне]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: Рівне
Triple: [Rovno, standardizedNameInUkrainian, Рівне]

Generated description

Рівне is a city in western Ukraine that serves as the administrative center of Rivne Oblast and an important regional economic and cultural hub.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: standardizedNameInUkrainian
Context triple: [Rovno, standardizedNameInUkrainian, Рівне]

A. hasOfficialNameInUkrainian
Indicates that an entity has an officially recognized name expressed in the Ukrainian language.
B. UkrainianName chosen
Indicates that an entity has a name that is in the Ukrainian language or follows Ukrainian naming conventions.
C. hasNameInRusyn
Indicates that an entity has a specific name or label expressed in the Rusyn language.
D. CyrillicName
Indicates that an entity has a name written in the Cyrillic script.
E. nameInLatinAlphabet
Indicates that an entity’s name is written or represented using the Latin alphabet.
F. None of above.

Provenance (6 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_69f34946a5208190bbd79f0fec4323bd`	completed	April 30, 2026, 12:21 p.m.
NER	Named-entity recognition	`batch_69f7c777e924819081a6634f549fe552`	completed	May 3, 2026, 10:08 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a34c69707bc8190a396eefd2adaead0`	completed	June 19, 2026, 4:33 a.m.
NEDg	Description generation	`batch_6a34c85cab748190abd850dca56c39ac`	completed	June 19, 2026, 4:41 a.m.
NED2	Entity disambiguation (via description)	`batch_6a34c93f41bc81908c366977b4f59d18`	completed	June 19, 2026, 4:44 a.m.
PD	Predicate disambiguation	`batch_69f7c475c58c8190a883554231e88c88`	completed	May 3, 2026, 9:56 p.m.

Created at: May 1, 2026, 1:19 a.m.