Triple

T28415929
Position Surface form Disambiguated ID Type / Status
Subject Spanish Fork E719803 entity
Predicate hasGeographicFeature P940 FINISHED
Object Lake Shore (nearby community)
Lake Shore is a small rural community in Utah County, Utah, situated near Spanish Fork and known for its agricultural character and proximity to Utah Lake.
E1817510 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: Lake Shore (nearby community) | Statement: [Spanish Fork, hasGeographicFeature, Lake Shore (nearby community)]
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: Lake Shore (nearby community)
Triple: [Spanish Fork, hasGeographicFeature, Lake Shore (nearby community)]
Generated description
Lake Shore is a small rural community in Utah County, Utah, situated near Spanish Fork and known for its agricultural character and proximity to Utah Lake.

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_69eff6f0f37c8190b37bc6fab08a9449 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64dc18ab081908ea8baa9edec31e2 completed May 2, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16331a141c8190b8c03a0ab2150892 completed May 26, 2026, 11:56 p.m.
NEDg Description generation batch_6a1633f6ab3c819084c6626f012a75da completed May 26, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a16350e130c8190a9a73ee1edce0928 completed May 27, 2026, 12:04 a.m.
Created at: April 28, 2026, 1:30 a.m.