Triple

T34910541
Position Surface form Disambiguated ID Type / Status
Subject Memorial Park (San Mateo County) E1006850 entity
Predicate near P350 FINISHED
Object Loma Mar, California
Loma Mar, California is a small unincorporated community in San Mateo County nestled in the forested Santa Cruz Mountains near popular redwood parks.
E2116213 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: Loma Mar, California | Statement: [Memorial Park (San Mateo County), near, Loma Mar, California]
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: Loma Mar, California
Triple: [Memorial Park (San Mateo County), near, Loma Mar, California]
Generated description
Loma Mar, California is a small unincorporated community in San Mateo County nestled in the forested Santa Cruz Mountains near popular redwood parks.

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_69f76dc1b4a081909b4c6e4d8ec0aa2d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7820e2f348190a904bcb407de549e completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786f097fc8190ab2b442bd6c7c556 completed June 21, 2026, 6:38 a.m.
NEDg Description generation batch_6a3790a2977081909d171a4bcea302fc completed June 21, 2026, 7:20 a.m.
NED2 Entity disambiguation (via description) batch_6a379170ec24819082c79ec7724c67e9 completed June 21, 2026, 7:23 a.m.
Created at: May 3, 2026, 4 p.m.