Triple

T30063951
Position Surface form Disambiguated ID Type / Status
Subject Powell Street, San Francisco E763973 entity
Predicate intersects P1018 FINISHED
Object Post Street, San Francisco
Post Street in San Francisco is a major east–west thoroughfare in the city's downtown and Union Square areas, known for its retail shops, hotels, and historic urban streetscape.
 E1915109 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: Post Street, San Francisco | Statement: [Powell Street, San Francisco, intersects, Post Street, San Francisco]
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: Post Street, San Francisco
Triple: [Powell Street, San Francisco, intersects, Post Street, San Francisco]
Generated description
Post Street in San Francisco is a major east–west thoroughfare in the city's downtown and Union Square areas, known for its retail shops, hotels, and historic urban streetscape.

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_69f2247221388190a13a22c47094a0ef completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ca5a1008190880f6da9f69c263b completed May 2, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27989626c88190b65e6f74fc93f55f completed June 9, 2026, 4:37 a.m.
NEDg Description generation batch_6a2799ef19948190845d5b3bfdda101b completed June 9, 2026, 4:43 a.m.
NED2 Entity disambiguation (via description) batch_6a279abfea348190b8a304523e458930 completed June 9, 2026, 4:46 a.m.
Created at: April 29, 2026, 6:58 p.m.