Triple

T34080336
Position Surface form Disambiguated ID Type / Status
Subject Archbishop of San Francisco E874019 entity
Predicate residence P75 FINISHED
Object San Francisco
San Francisco is a major cultural, financial, and technological hub in Northern California, known for its iconic Golden Gate Bridge, steep hills, and historic role in the development of the tech industry.
E242 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: San Francisco | Statement: [Archbishop of San Francisco, residence, 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: San Francisco
Triple: [Archbishop of San Francisco, residence, San Francisco]
Generated description
San Francisco is a major cultural, financial, and technological hub in Northern California, known for its iconic Golden Gate Bridge, steep hills, and historic role in the development of the tech industry.

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_69f349a61d448190b74642f325d3eb7a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70bd625f081909808d25ca555e510 completed May 3, 2026, 8:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36ae4ba4e881908c1db6ba15fb80c8 completed June 20, 2026, 3:14 p.m.
NEDg Description generation batch_6a36aef5e62c81909695813abde97094 completed June 20, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36afe4c5cc81909ea9c8b3d3903db5 completed June 20, 2026, 3:21 p.m.
Created at: May 1, 2026, 1:52 a.m.