Triple

T30627627

Position	Surface form	Disambiguated ID	Type / Status
Subject	U Bundestag	`E779625`	entity
Predicate	servedByLineSince	`P1293`	FINISHED
Object	U55 U55 was a short Berlin U-Bahn shuttle line that connected the city’s main railway station with central government and parliamentary districts before being integrated into line U5.	`E530780`	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: U55 | Statement: [U Bundestag, servedByLineSince, U55]

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: U55
Triple: [U Bundestag, servedByLineSince, U55]

Generated description

U55 was a short Berlin U-Bahn shuttle line that connected the city’s main railway station with central government and parliamentary districts before being integrated into line U5.

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

Target predicate: servedByLineSince
Context triple: [U Bundestag, servedByLineSince, U55]

A. servesLineSince
Indicates that a transportation service or route has been operating on a particular line since a specified point in time.
B. servedByLine chosen
Indicates that a transportation stop, station, or location is provided service by a specific transit line.
C. formerLineServed
Indicates that a particular transit line previously provided service to a route, station, or area but no longer does so.
D. servedUntil
Indicates the ending time or date up to which an entity held a position, role, or service.
E. laterServedBy
Indicates that one entity is subsequently served or provided service by another entity at a later time.
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_69f224a431548190a44ad9d088dbf91f`	completed	April 29, 2026, 3:32 p.m.
NER	Named-entity recognition	`batch_69fe991bca608190b524e419642f4243`	completed	May 9, 2026, 2:16 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2863ea6170819088bf5a407f6eb97c`	completed	June 9, 2026, 7:05 p.m.
NEDg	Description generation	`batch_6a28683a08c48190992c65e4ebd02e56`	completed	June 9, 2026, 7:23 p.m.
NED2	Entity disambiguation (via description)	`batch_6a2868fa5d1c81909ec9422f7d152a75`	completed	June 9, 2026, 7:26 p.m.
PD	Predicate disambiguation	`batch_69fe979fc1c4819091fc48d63ea12063`	completed	May 9, 2026, 2:10 a.m.

Created at: April 29, 2026, 8:28 p.m.