Triple

T31618489
Position Surface form Disambiguated ID Type / Status
Subject Country Place E806828 entity
Predicate followsWorkBySameAuthor P28586 FINISHED
Object The Street
The Street is a novel by Ann Petry that powerfully portrays the struggles of a Black woman facing racism, sexism, and poverty in 1940s Harlem.
 E806822 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: The Street | Statement: [Country Place, followsWorkBySameAuthor, The Street]
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: The Street
Triple: [Country Place, followsWorkBySameAuthor, The Street]
Generated description
The Street is a novel by Ann Petry that powerfully portrays the struggles of a Black woman facing racism, sexism, and poverty in 1940s Harlem.

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_69f348d7883c8190b6c13ab92b7ef076 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a8acae308190b3450346a6bb55bc completed May 3, 2026, 1:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84a85ed08190bbba270a575ed3da completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b85d549e08190836ce42497053d25 completed June 12, 2026, 4:06 a.m.
NED2 Entity disambiguation (via description) batch_6a2b86d3c0d88190ab770b24411e06e4 completed June 12, 2026, 4:10 a.m.
Created at: April 30, 2026, 10:40 p.m.