Triple

T24782785
Position Surface form Disambiguated ID Type / Status
Subject Prytania Street and Coliseum Street E620043 entity
Predicate hasStreet P959 FINISHED
Object Coliseum Street
Coliseum Street is a roadway in New Orleans, Louisiana, known for running through the historic Uptown area lined with 19th-century homes and oak trees.
 E1651648 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: Coliseum Street | Statement: [Prytania Street and Coliseum Street, hasStreet, Coliseum 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: Coliseum Street
Triple: [Prytania Street and Coliseum Street, hasStreet, Coliseum Street]
Generated description
Coliseum Street is a roadway in New Orleans, Louisiana, known for running through the historic Uptown area lined with 19th-century homes and oak trees.

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_69e2fabdbe8c8190adbb9434b8636cad completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410d73b288190995b2ada5788f436 completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c2357fc8190bb048035797afc9f completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a1025b941fc819081957c8e7d21b7f1 completed May 22, 2026, 9:45 a.m.
NED2 Entity disambiguation (via description) batch_6a10265a02e08190b628804a79f31882 completed May 22, 2026, 9:48 a.m.
Created at: April 18, 2026, 4:45 a.m.