Triple

T26620803

Position	Surface form	Disambiguated ID	Type / Status
Subject	Ploshchad Alexandra Nevskogo I	`E668189`	entity
Predicate	hasTransferToStation	`P98214`	FINISHED
Object	Ploshchad Alexandra Nevskogo II Ploshchad Alexandra Nevskogo II is a station on the Saint Petersburg Metro, forming part of the Ploshchad Alexandra Nevskogo interchange complex.	`E668189`	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: Ploshchad Alexandra Nevskogo II | Statement: [Ploshchad Alexandra Nevskogo I, hasTransferToStation, Ploshchad Alexandra Nevskogo II]

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: Ploshchad Alexandra Nevskogo II
Triple: [Ploshchad Alexandra Nevskogo I, hasTransferToStation, Ploshchad Alexandra Nevskogo II]

Generated description

Ploshchad Alexandra Nevskogo II is a station on the Saint Petersburg Metro, forming part of the Ploshchad Alexandra Nevskogo interchange complex.

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

Target predicate: hasTransferToStation
Context triple: [Ploshchad Alexandra Nevskogo I, hasTransferToStation, Ploshchad Alexandra Nevskogo II]

A. hasTransfer
Indicates a relationship where something is moved or conveyed from one entity or location to another.
B. hasTransferToService
Indicates that something includes or involves a transfer directed to a particular service.
C. hasInterchangeStationWith chosen
Indicates that two transportation lines, routes, or systems share a station where passengers can transfer between them.
D. hasTopStation
Indicates that an entity is associated with or connected to a specific station that is designated as its top or uppermost station.
E. isTransferStationWith
Indicates that a station functions as an intermediate transfer point where passengers or goods can switch between different routes, lines, or modes of transport.
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_69ee9cfe16088190a3dddd68e3c7b1ea`	completed	April 26, 2026, 11:17 p.m.
NER	Named-entity recognition	`batch_69f79f48acec8190a9d5964581a94f6c`	completed	May 3, 2026, 7:17 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a12092b1ccc81908e5e214ee43b83db`	completed	May 23, 2026, 8:08 p.m.
NEDg	Description generation	`batch_6a120aa69a8c819083a6dc95e4d6382e`	completed	May 23, 2026, 8:14 p.m.
NED2	Entity disambiguation (via description)	`batch_6a120b329b30819089e007135e13dc21`	completed	May 23, 2026, 8:16 p.m.
PD	Predicate disambiguation	`batch_69f79e4888248190be2f63cdfb5cd7b7`	completed	May 3, 2026, 7:13 p.m.

Created at: April 27, 2026, 2:20 a.m.