Triple

T29991997
Position Surface form Disambiguated ID Type / Status
Subject PS 397 Spruce Street School E761904 entity
Predicate alsoKnownAs P39 FINISHED
Object Spruce Street School
Spruce Street School is a New York City public elementary school known for its focus on progressive, community-centered education in Lower Manhattan.
 E1908654 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: Spruce Street School | Statement: [PS 397 Spruce Street School, alsoKnownAs, Spruce Street School]
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: Spruce Street School
Triple: [PS 397 Spruce Street School, alsoKnownAs, Spruce Street School]
Generated description
Spruce Street School is a New York City public elementary school known for its focus on progressive, community-centered education in Lower Manhattan.

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_69f224695498819094a81037cad401e2 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6791b73a081908c15d046673bbc37 completed May 2, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ed954488190b3f6f3fbbf0b6db3 completed June 9, 2026, 1:39 a.m.
NEDg Description generation batch_6a2772b62b348190b3d1bf268a901288 completed June 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_6a2772eb8538819087415acface6f03c completed June 9, 2026, 1:56 a.m.
Created at: April 29, 2026, 6:39 p.m.