Triple

T36265045
Position Surface form Disambiguated ID Type / Status
Subject Frog Music E892197 entity
Predicate setInLocation P40 FINISHED
Object San Francisco
San Francisco is a major coastal city in Northern California known for its steep hills, iconic Golden Gate Bridge, diverse culture, and historic role in technology and counterculture movements.
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: [Frog Music, setInLocation, 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: [Frog Music, setInLocation, San Francisco]
Generated description
San Francisco is a major coastal city in Northern California known for its steep hills, iconic Golden Gate Bridge, diverse culture, and historic role in technology and counterculture movements.

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_69f76e4699188190af045b11a840ce31 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b625b090819095a9db9382211af7 completed May 3, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a396dff13448190a3c391996dc1e928 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a396f2486448190a257c95156f40ef7 completed June 22, 2026, 5:21 p.m.
NED2 Entity disambiguation (via description) batch_6a396f9eec788190a90ba0850106036f completed June 22, 2026, 5:23 p.m.
Created at: May 3, 2026, 4:09 p.m.