Triple

T27787022
Position Surface form Disambiguated ID Type / Status
Subject Lahav Shani E700988 entity
Predicate educatedAt P5 FINISHED
Object Thelma Yellin High School of the Arts
Thelma Yellin High School of the Arts is a prestigious Israeli secondary school renowned for its intensive, pre-professional training in music, dance, theater, and visual arts.
E1788820 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: Thelma Yellin High School of the Arts | Statement: [Lahav Shani, educatedAt, Thelma Yellin High School of the Arts]
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: Thelma Yellin High School of the Arts
Triple: [Lahav Shani, educatedAt, Thelma Yellin High School of the Arts]
Generated description
Thelma Yellin High School of the Arts is a prestigious Israeli secondary school renowned for its intensive, pre-professional training in music, dance, theater, and visual arts.

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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f637d2e5e08190bc1708336a4fbfc5 completed May 2, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecc87820819087ccedcdc404d30b completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed68ab588190a2247672cc7818d8 completed May 24, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee56948881908c58657e262882a0 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 5:25 p.m.