Triple

T26531349

Position	Surface form	Disambiguated ID	Type / Status
Subject	Kesswil railway station	`E670826`	entity
Predicate	lineOn	`P17813`	FINISHED
Object	Lake line Lake line is a Swiss railway route that runs along the southern shore of Lake Constance, connecting various towns in the northeastern part of the country.	`E1729645`	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: Lake line | Statement: [Kesswil railway station, lineOn, Lake line]

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: Lake line
Triple: [Kesswil railway station, lineOn, Lake line]

Generated description

Lake line is a Swiss railway route that runs along the southern shore of Lake Constance, connecting various towns in the northeastern part of the country.

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

Target predicate: lineOn
Context triple: [Kesswil railway station, lineOn, Lake line]

A. lineUse
Indicates how a particular line (such as a route, track, or service line) is utilized or purposed within a system or network.
B. lineStandard
Indicates that one entity is a standard or reference specification that defines or governs the characteristics or requirements of a particular line (such as a product line, production line, or service line).
C. lineExample
Indicates that one entity serves as an illustrative or representative example of a particular line, sequence, or linear construct associated with another entity.
D. lineElement chosen
Indicates a relationship where something functions as, or is identified as, an element or segment of a line within a larger linear structure or representation.
E. lineProduced
Indicates that one entity (such as a production line or process) generated, manufactured, or output the other entity.
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_69eeb31ea1e08190b9ff43cf9bc25bf8`	completed	April 27, 2026, 12:51 a.m.
NER	Named-entity recognition	`batch_69f613f84cdc8190828985c94d8491d5`	completed	May 2, 2026, 3:10 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a11bb4f014481909fedcd2da6cb9321`	completed	May 23, 2026, 2:35 p.m.
NEDg	Description generation	`batch_6a11be7299bc8190af51631bdd281189`	completed	May 23, 2026, 2:49 p.m.
NED2	Entity disambiguation (via description)	`batch_6a11c0f6af5081908a7e32353c41ab76`	completed	May 23, 2026, 3 p.m.
PD	Predicate disambiguation	`batch_69f602d7b1b0819095ddd3b5169f8ce2`	completed	May 2, 2026, 1:57 p.m.

Created at: April 27, 2026, 1:35 a.m.