Triple

T32299732
Position Surface form Disambiguated ID Type / Status
Subject Edward J. Corsi E825202 entity
Predicate fullName P16 FINISHED
Object Edward Julius Corsi
Edward Julius Corsi was an Italian-born American politician and public official known for his work on immigration and labor issues in the mid-20th century United States.
 E2001671 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: Edward Julius Corsi | Statement: [Edward J. Corsi, fullName, Edward Julius Corsi]
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: Edward Julius Corsi
Triple: [Edward J. Corsi, fullName, Edward Julius Corsi]
Generated description
Edward Julius Corsi was an Italian-born American politician and public official known for his work on immigration and labor issues in the mid-20th century United States.

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_69f349115304819084ee91d345b6c8aa completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bd70b43c819086d1e5f1df5aec86 completed May 3, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a30570a2f2881908f27137c9bc702c1 completed June 15, 2026, 7:48 p.m.
NEDg Description generation batch_6a305ad097f481908935fa484b3aba59 completed June 15, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_6a305b7872348190aaa5fd5c7eb1a955 completed June 15, 2026, 8:07 p.m.
Created at: May 1, 2026, 12:45 a.m.