Triple

T35991942
Position Surface form Disambiguated ID Type / Status
Subject Nannie Louise Perry Hansberry E1040869 entity
Predicate birthName P65 FINISHED
Object Nannie Louise Perry
Nannie Louise Perry was the mother of playwright Lorraine Hansberry and a member of a prominent African American family active in civil rights and Chicago community life.
E2165873 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: Nannie Louise Perry | Statement: [Nannie Louise Perry Hansberry, birthName, Nannie Louise Perry]
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: Nannie Louise Perry
Triple: [Nannie Louise Perry Hansberry, birthName, Nannie Louise Perry]
Generated description
Nannie Louise Perry was the mother of playwright Lorraine Hansberry and a member of a prominent African American family active in civil rights and Chicago community life.

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_69f76e29084c819083987b828d414de7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac5bbc4081909277a22b6b1dbba6 completed May 3, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfe9f4448190b271097193ead28a completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c3bffd888190b9cb3baed991ea3a completed June 22, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_6a38c437221c81909bbe2678714092f8 completed June 22, 2026, 5:12 a.m.
Created at: May 3, 2026, 4:07 p.m.