Triple

T23755750

Position	Surface form	Disambiguated ID	Type / Status
Subject	Fort Totten station (Washington Metro)	`E587109`	entity
Predicate	addedService	`P4097`	FINISHED
Object	Green Line The Green Line is one of the primary lines of the Washington Metro rapid transit system, running generally north–south through Washington, D.C. and into Maryland.	`E13654`	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: Green Line | Statement: [Fort Totten station (Washington Metro), addedService, Green 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: Green Line
Triple: [Fort Totten station (Washington Metro), addedService, Green Line]

Generated description

The Green Line is one of the primary lines of the Washington Metro rapid transit system, running generally north–south through Washington, D.C. and into Maryland.

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

Target predicate: addedService
Context triple: [Fort Totten station (Washington Metro), addedService, Green Line]

A. introducedToService
Indicates that one entity has presented or brought another entity into contact with a particular service for the first time.
B. serviceIntroduced
Indicates that a particular service has been launched, made available, or brought into operation at a certain time or context.
C. addedFor
Indicates that one entity was created, included, or introduced specifically for the benefit, use, or purpose of another entity.
D. addedTo chosen
Indicates that one entity has been included or incorporated into another entity, typically as a new component, member, or element.
E. serviceWith
Indicates that one entity provides or is associated with a particular service offered to or used by another 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_69e2490a0eec81908cdef8a862828d7a`	completed	April 17, 2026, 2:51 p.m.
NER	Named-entity recognition	`batch_69f1bdab86108190becd7f27650082cc`	completed	April 29, 2026, 8:13 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0fc98f70288190bc2b3896d4642f30`	completed	May 22, 2026, 3:12 a.m.
NEDg	Description generation	`batch_6a0fcb41ec208190ab3fb4e8b52c8c81`	completed	May 22, 2026, 3:19 a.m.
NED2	Entity disambiguation (via description)	`batch_6a0fcbb4883c81909bb9f02361c69fe7`	completed	May 22, 2026, 3:21 a.m.
PD	Predicate disambiguation	`batch_69f155f79e34819080f9ddb972b34deb`	completed	April 29, 2026, 12:51 a.m.

Created at: April 17, 2026, 7:14 p.m.