Triple

T32818522
Position Surface form Disambiguated ID Type / Status
Subject unincorporated Rossmoor, California E839367 entity
Predicate hasFeature P182 FINISHED
Object Rossmoor Shopping Center
Rossmoor Shopping Center is a local retail and service hub serving the community of unincorporated Rossmoor in Orange County, California.
E2023035 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: Rossmoor Shopping Center | Statement: [unincorporated Rossmoor, California, hasFeature, Rossmoor Shopping Center]
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: Rossmoor Shopping Center
Triple: [unincorporated Rossmoor, California, hasFeature, Rossmoor Shopping Center]
Generated description
Rossmoor Shopping Center is a local retail and service hub serving the community of unincorporated Rossmoor in Orange County, California.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdd27c44819091d45e31f4b67e64 completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b17fdea88190a6cc2c65c56e3358 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b260c0348190a57ea60a6683be16 completed June 19, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_6a34b2e5c568819099352545177c81b7 completed June 19, 2026, 3:09 a.m.
Created at: May 1, 2026, 1:15 a.m.