Triple

T30231629
Position Surface form Disambiguated ID Type / Status
Subject Brown stages of language development E768643 entity
Predicate originalDataCollectedFrom P201762 FINISHED
Object Eve
Eve is a child whose early speech was extensively recorded and analyzed, providing foundational data for Roger Brown’s influential stages of language development in children.
E1905431 NE FINISHED

How this triple was built (2 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: Eve | Statement: [Brown stages of language development, originalDataCollectedFrom, Eve]
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: Eve
Triple: [Brown stages of language development, originalDataCollectedFrom, Eve]
Generated description
Eve is a child whose early speech was extensively recorded and analyzed, providing foundational data for Roger Brown’s influential stages of language development in children.

Provenance (5 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_6a00218a4dc08190bbf4c4334b9d9631 completed May 10, 2026, 6:11 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.
Created at: April 29, 2026, 7:36 p.m.