Triple

T28667008

Position	Surface form	Disambiguated ID	Type / Status
Subject	Professor George Gammell Angell	`E725609`	entity
Predicate	documentTypeAssociated	`P19006`	FINISHED
Object	Angell papers The Angell papers are a collection of documents and research materials associated with Professor George Gammell Angell, notably tied to his investigations into esoteric and occult phenomena.	`E1828385`	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: Angell papers | Statement: [Professor George Gammell Angell, documentTypeAssociated, Angell papers]

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: Angell papers
Triple: [Professor George Gammell Angell, documentTypeAssociated, Angell papers]

Generated description

The Angell papers are a collection of documents and research materials associated with Professor George Gammell Angell, notably tied to his investigations into esoteric and occult phenomena.

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

Target predicate: documentTypeAssociated
Context triple: [Professor George Gammell Angell, documentTypeAssociated, Angell papers]

A. documentTypeUsed
Indicates that a particular type or category of document is employed or applied in a given context or activity.
B. documentationType chosen
Indicates the specific category or kind of documentation associated with or required for an entity or process.
C. documentTypeIncluded
Indicates that a particular document type is contained within, or is part of, a specified set or collection of document types.
D. documentTypeContext
Indicates the contextual relationship between a document and its specific type or classification within a given setting or usage scenario.
E. documentsTypeOfStructure
Indicates that an entity records or specifies the particular type or classification of a structure.
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_69f01d85be388190b669a0e401e2f2c4`	completed	April 28, 2026, 2:37 a.m.
NER	Named-entity recognition	`batch_69f67c9fe7b48190b79b4041357edb49`	completed	May 2, 2026, 10:37 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a1cc395a1a88190877ee0a155d4b3eb`	completed	May 31, 2026, 11:26 p.m.
NEDg	Description generation	`batch_6a1cc463bda48190bec84f370b367cff`	completed	May 31, 2026, 11:29 p.m.
NED2	Entity disambiguation (via description)	`batch_6a1cc5027a4881908055cfa03af83b64`	completed	May 31, 2026, 11:32 p.m.
PD	Predicate disambiguation	`batch_69f678cc272081909e5c70f1bc7407f0`	completed	May 2, 2026, 10:21 p.m.

Created at: April 28, 2026, 5:01 a.m.