Triple

T35127106

Position	Surface form	Disambiguated ID	Type / Status
Subject	SKM Tricity	`E1014336`	entity
Predicate	primaryRollingStockModel	`P1305`	FINISHED
Object	EN57 EN57 is a long-serving Polish electric multiple unit train class widely used for regional and suburban passenger services across Poland.	`E2126093`	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: EN57 | Statement: [SKM Tricity, primaryRollingStockModel, EN57]

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: EN57
Triple: [SKM Tricity, primaryRollingStockModel, EN57]

Generated description

EN57 is a long-serving Polish electric multiple unit train class widely used for regional and suburban passenger services across Poland.

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

Target predicate: primaryRollingStockModel
Context triple: [SKM Tricity, primaryRollingStockModel, EN57]

A. ownedRollingStock
Indicates that one entity possesses or has ownership rights over specific rolling stock (such as trains, railcars, or locomotives).
B. passengerRollingStock
Indicates that the rolling stock is designed or used for carrying passengers rather than freight or other purposes.
C. formerRollingStock
Indicates that an entity was previously used as rolling stock (e.g., railway vehicles) but no longer serves in that capacity.
D. rollingStockType chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
E. introducedRollingStock
Indicates that an entity caused new rolling stock (such as trains or rail vehicles) to be put into service or use.
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_69f76dd8b6948190aaa32b081816bd94`	completed	May 3, 2026, 3:46 p.m.
NER	Named-entity recognition	`batch_6a037c8c34f88190ace26f555827f23e`	completed	May 12, 2026, 7:16 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37d00b0ad48190967d8f1308c75dbf`	completed	June 21, 2026, 11:50 a.m.
NEDg	Description generation	`batch_6a37d09160108190adcf3b1a85a0e8a2`	completed	June 21, 2026, 11:52 a.m.
NED2	Entity disambiguation (via description)	`batch_6a37d1d5dad081908a0f25b28428977b`	completed	June 21, 2026, 11:58 a.m.
PD	Predicate disambiguation	`batch_6a037a016960819093ed4990fb4d9d36`	completed	May 12, 2026, 7:05 p.m.

Created at: May 3, 2026, 4:02 p.m.