Triple

T32441641
Position Surface form Disambiguated ID Type / Status
Subject Laguna Beach City Council E829028 entity
Predicate meetsAt P373 FINISHED
Object Laguna Beach City Hall
Laguna Beach City Hall is the primary municipal government building for the city of Laguna Beach, California, housing key administrative offices and public meeting spaces.
E2005780 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: Laguna Beach City Hall | Statement: [Laguna Beach City Council, meetsAt, Laguna Beach City Hall]
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: Laguna Beach City Hall
Triple: [Laguna Beach City Council, meetsAt, Laguna Beach City Hall]
Generated description
Laguna Beach City Hall is the primary municipal government building for the city of Laguna Beach, California, housing key administrative offices and public meeting spaces.

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_69f3491d2e5c819092b1c9535beff8ec completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e310788190b57a9adbda4dd895 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f3658708190b9c31ca163117f19 completed June 18, 2026, 8:04 p.m.
NEDg Description generation batch_6a3453206fb081908b641a4a804eb814 completed June 18, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a34538c05708190a42d883a62a92893 completed June 18, 2026, 8:22 p.m.
Created at: May 1, 2026, 12:55 a.m.