Triple

T33445729
Position Surface form Disambiguated ID Type / Status
Subject Single Ladies E856492 entity
Predicate hasSetting P3538 FINISHED
Object contemporary Atlanta
Contemporary Atlanta is the modern, culturally vibrant urban setting of the television series "Single Ladies," known for its dynamic blend of Southern charm, fashion, and nightlife.
E2051246 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: contemporary Atlanta | Statement: [Single Ladies, hasSetting, contemporary Atlanta]
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: contemporary Atlanta
Triple: [Single Ladies, hasSetting, contemporary Atlanta]
Generated description
Contemporary Atlanta is the modern, culturally vibrant urban setting of the television series "Single Ladies," known for its dynamic blend of Southern charm, fashion, and nightlife.

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_69f34971b75881908be360bb041f003c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e4a7497c8190be81f04e99b769d4 completed May 3, 2026, 6:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a358160a1a481909679886068e85358 completed June 19, 2026, 5:50 p.m.
NEDg Description generation batch_6a358270a84081909f9defde3b895271 completed June 19, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_6a3582d601608190922e504f24bb2061 completed June 19, 2026, 5:56 p.m.
Created at: May 1, 2026, 1:37 a.m.