Triple

T34771622

Position	Surface form	Disambiguated ID	Type / Status
Subject	L0 Series maglev trainsets	`E1002376`	entity
Predicate	plannedCommercialRoute	`P191605`	FINISHED
Object	Tokyo–Nagoya Tokyo–Nagoya is a major high-speed rail corridor in Japan connecting the capital Tokyo with the industrial and commercial hub of Nagoya.	`E359588`	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: Tokyo–Nagoya | Statement: [L0 Series maglev trainsets, plannedCommercialRoute, Tokyo–Nagoya]

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: Tokyo–Nagoya
Triple: [L0 Series maglev trainsets, plannedCommercialRoute, Tokyo–Nagoya]

Generated description

Tokyo–Nagoya is a major high-speed rail corridor in Japan connecting the capital Tokyo with the industrial and commercial hub of Nagoya.

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

Target predicate: plannedCommercialRoute
Context triple: [L0 Series maglev trainsets, plannedCommercialRoute, Tokyo–Nagoya]

A. flightRoute
Indicates a path or sequence of locations that a particular flight travels between, typically from its origin to its destination (and possibly via intermediate stops).
B. operatesLongHaulRouteFrom
Indicates that an entity (typically a transportation carrier) runs long-distance routes originating from a specified location.
C. primaryMarketedRouteName
Indicates the main route or method by which a product is marketed or delivered to its intended users.
D. operatedRoutes
Indicates that an agent (such as a company or organization) runs or manages specific routes, typically providing services along those paths.
E. primaryAirlineRoutesTo
Indicates that one airline serves as the main carrier operating direct or regular flight routes to a particular destination or airport.
F. None of above. chosen

Provenance (7 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_69f76db20dac8190b1e8d0ca4dc1d59f`	completed	May 3, 2026, 3:45 p.m.
NER	Named-entity recognition	`batch_69fce28d6c3081908bf76f5db63ecf68`	completed	May 7, 2026, 7:05 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37663b51cc81908f96fe1ace529ccb`	completed	June 21, 2026, 4:19 a.m.
NEDg	Description generation	`batch_6a3766c62020819090092f8f0de60644`	completed	June 21, 2026, 4:21 a.m.
NED2	Entity disambiguation (via description)	`batch_6a37673026e881908b26f42f12f81b2f`	completed	June 21, 2026, 4:23 a.m.
PD	Predicate disambiguation	`batch_69fce12d2f08819082134b5eb3db6a24`	completed	May 7, 2026, 6:59 p.m.
PDg	Predicate description generation	`batch_69fce28a74508190aab36551094e8226`	completed	May 7, 2026, 7:05 p.m.

Created at: May 3, 2026, 3:59 p.m.