Triple

T33713324

Position	Surface form	Disambiguated ID	Type / Status
Subject	Langhus	`E863801`	entity
Predicate	hasLibraryServiceFrom	`P97932`	FINISHED
Object	Nordre Follo public library Nordre Follo public library is the municipal library system serving residents of Nordre Follo, Norway, offering access to books, digital media, and community services across its branches.	`E2064150`	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: Nordre Follo public library | Statement: [Langhus, hasLibraryServiceFrom, Nordre Follo public library]

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: Nordre Follo public library
Triple: [Langhus, hasLibraryServiceFrom, Nordre Follo public library]

Generated description

Nordre Follo public library is the municipal library system serving residents of Nordre Follo, Norway, offering access to books, digital media, and community services across its branches.

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

Target predicate: hasLibraryServiceFrom
Context triple: [Langhus, hasLibraryServiceFrom, Nordre Follo public library]

A. hasLibraries
Indicates that an entity possesses, contains, or is associated with one or more libraries.
B. hasOfficialLibrary
Indicates that an entity possesses or is served by a formally recognized, authorized library.
C. hasServiceTo
Indicates that one entity provides, offers, or operates a service for or directed toward another entity.
D. hasLibraryBranch
Indicates that an entity possesses or is associated with one or more library branches as part of its organizational structure or services.
E. servedByLibrary chosen
Indicates that an entity receives services, resources, or support from a particular library.
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_69f3498844608190bb8f9b14908d2510`	completed	April 30, 2026, 12:22 p.m.
NER	Named-entity recognition	`batch_69fe30bc64308190b603ff1b30c2aeee`	completed	May 8, 2026, 6:51 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a363ca78aec8190bc179bf0f30da38e`	completed	June 20, 2026, 7:09 a.m.
NEDg	Description generation	`batch_6a365674ecb481909f0e56ce3277c6b4`	completed	June 20, 2026, 8:59 a.m.
NED2	Entity disambiguation (via description)	`batch_6a3656e722f48190b33ac5217c8a9921`	completed	June 20, 2026, 9:01 a.m.
PD	Predicate disambiguation	`batch_69fe2f7175b081908dd61e1513620bbe`	completed	May 8, 2026, 6:46 p.m.

Created at: May 1, 2026, 1:43 a.m.