Triple

T38261697

Position	Surface form	Disambiguated ID	Type / Status
Subject	42 London	`E1017943`	entity
Predicate	hasGlobalAffiliation	`P190779`	FINISHED
Object	42 Foundation 42 Foundation is an international nonprofit organization that operates a global network of tuition-free, peer-to-peer coding schools, including 42 London.	`E2263165`	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: 42 Foundation | Statement: [42 London, hasGlobalAffiliation, 42 Foundation]

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: 42 Foundation
Triple: [42 London, hasGlobalAffiliation, 42 Foundation]

Generated description

42 Foundation is an international nonprofit organization that operates a global network of tuition-free, peer-to-peer coding schools, including 42 London.

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

Target predicate: hasGlobalAffiliation
Context triple: [42 London, hasGlobalAffiliation, 42 Foundation]

A. hasAffiliationScope
Indicates the scope or extent within which an affiliation or association between entities is valid or applies.
B. hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
C. hadInternationalAffiliation
Indicates that an entity was formally associated or connected with an organization, institution, or body based in a foreign country or operating across national borders.
D. hasRegionalAffiliation
Indicates that an entity is associated with, belongs to, or is officially linked to a specific geographic region.
E. holderAffiliation
Indicates that a holder (such as a person or organization) is affiliated with, or belongs to, a particular group, institution, or entity.
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_69f76de33e4481909099fa812709bd42`	completed	May 3, 2026, 3:46 p.m.
NER	Named-entity recognition	`batch_69fcd1499e2c81909bafd84dc4810f45`	completed	May 7, 2026, 5:52 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a4193d4e2408190bd8893fc769eaaa2`	completed	June 28, 2026, 9:36 p.m.
NEDg	Description generation	`batch_6a41947a2f608190aba9f20c7e4cd8d6`	completed	June 28, 2026, 9:39 p.m.
NED2	Entity disambiguation (via description)	`batch_6a4195210170819086828d7780a6e407`	completed	June 28, 2026, 9:41 p.m.
PD	Predicate disambiguation	`batch_69fcccf024ec819086383ffbb6cfc036`	completed	May 7, 2026, 5:33 p.m.
PDg	Predicate description generation	`batch_69fcd148e6d4819082c118832ecc599b`	completed	May 7, 2026, 5:52 p.m.

Created at: May 3, 2026, 4:30 p.m.