Triple

T34616680

Position	Surface form	Disambiguated ID	Type / Status
Subject	EMD 645 series	`E888882`	entity
Predicate	usedInLocomotiveModel	`P156871`	FINISHED
Object	EMD SD40 The EMD SD40 is a six-axle, 3,000-horsepower diesel-electric freight locomotive built by Electro-Motive Division that became one of the most widely used and influential North American road locomotives of the late 1960s and 1970s.	`E2108379`	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: EMD SD40 | Statement: [EMD 645 series, usedInLocomotiveModel, EMD SD40]

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: EMD SD40
Triple: [EMD 645 series, usedInLocomotiveModel, EMD SD40]

Generated description

The EMD SD40 is a six-axle, 3,000-horsepower diesel-electric freight locomotive built by Electro-Motive Division that became one of the most widely used and influential North American road locomotives of the late 1960s and 1970s.

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

Target predicate: usedInLocomotiveModel
Context triple: [EMD 645 series, usedInLocomotiveModel, EMD SD40]

A. usedInLocomotiveSeries chosen
Indicates that something is employed or implemented within a particular locomotive series.
B. usedLocomotives
Indicates that an entity employed locomotives as tools, resources, or means to perform an action or fulfill a function.
C. hasLocomotive
Indicates that one entity possesses or is equipped with a locomotive as part of its composition or operation.
D. laterLocomotiveType
Indicates that one locomotive type succeeds or comes after another in time, representing a later development or version in locomotive design.
E. locomotiveWorks
Indicates a relationship where an entity is a facility or company that builds, repairs, or maintains locomotives.
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_69f349d584e08190b40b9f6281ad50c4`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69fea2d0a4d08190aa06aeb902a02d5a`	completed	May 9, 2026, 2:58 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3752df3d64819093e78c47b95b9f2c`	completed	June 21, 2026, 2:56 a.m.
NEDg	Description generation	`batch_6a37547d30e48190be2b92edafa4bfb1`	completed	June 21, 2026, 3:03 a.m.
NED2	Entity disambiguation (via description)	`batch_6a3754e5d64881908b3014411b023fff`	completed	June 21, 2026, 3:05 a.m.
PD	Predicate disambiguation	`batch_69fea24698348190b9b992a8e7cdbcd0`	completed	May 9, 2026, 2:56 a.m.

Created at: May 1, 2026, 2:03 a.m.