Triple

T30231628

Position	Surface form	Disambiguated ID	Type / Status
Subject	Brown stages of language development	`E768643`	entity
Predicate	originalDataCollectedFrom	`P201762`	FINISHED
Object	Adam Adam is a child participant whose early speech and language use were extensively recorded and analyzed in Roger Brown’s classic longitudinal study of language development.	`E1905430`	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: Adam | Statement: [Brown stages of language development, originalDataCollectedFrom, Adam]

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: Adam
Triple: [Brown stages of language development, originalDataCollectedFrom, Adam]

Generated description

Adam is a child participant whose early speech and language use were extensively recorded and analyzed in Roger Brown’s classic longitudinal study of language development.

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

Target predicate: originalDataCollectedFrom
Context triple: [Brown stages of language development, originalDataCollectedFrom, Adam]

A. originalDataCollectedBy chosen
Indicates that the original data was gathered or recorded by a specified agent or source.
B. collectionOrigin
Indicates that one entity is the source, provenance, or originating context from which a collection of items or data has been derived or assembled.
C. collectedThrough
Indicates that something was obtained, gathered, or acquired by means of a specified process, method, or channel.
D. dataTypeCollected
Indicates that a specific type or category of data is gathered or recorded in the context of an entity or process.
E. collectsDataFor
Indicates that one entity gathers or records data on behalf of, or for the benefit of, 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_69f2248108208190be60bf1af343ce70`	completed	April 29, 2026, 3:32 p.m.
NER	Named-entity recognition	`batch_6a002103c93081908398fa5726f5fa6e`	completed	May 10, 2026, 6:09 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a27644757a8819082533f991fe1ac90`	completed	June 9, 2026, 12:54 a.m.
NEDg	Description generation	`batch_6a2765619d608190baff5be2c3c926e7`	completed	June 9, 2026, 12:59 a.m.
NED2	Entity disambiguation (via description)	`batch_6a27662ed7c88190837a024195b7accc`	completed	June 9, 2026, 1:02 a.m.
PD	Predicate disambiguation	`batch_6a001fcb9fb48190a27d8f2ca983fbe6`	completed	May 10, 2026, 6:03 a.m.

Created at: April 29, 2026, 7:36 p.m.