Triple

T23478864
Position Surface form Disambiguated ID Type / Status
Subject Nora Daley E570345 entity
Predicate relative P37 FINISHED
Object Vivian Daley
Vivian Daley is a member of the Daley family, related to Nora Daley, who is part of the prominent political Daley dynasty of Chicago.
E1665012 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: Vivian Daley | Statement: [Nora Daley, relative, Vivian Daley]
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: Vivian Daley
Triple: [Nora Daley, relative, Vivian Daley]
Generated description
Vivian Daley is a member of the Daley family, related to Nora Daley, who is part of the prominent political Daley dynasty of Chicago.

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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a74e7e648190b89006dce7d7ce05 completed April 29, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cabe3848190aa7d6817e0e4a228 completed May 22, 2026, 1:39 p.m.
NEDg Description generation batch_6a105daad81481909d399aba96a1176c completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105e3d647881909b04575cd240d468 completed May 22, 2026, 1:46 p.m.
Created at: April 17, 2026, 6:02 p.m.