Triple

T35468024
Position Surface form Disambiguated ID Type / Status
Subject Algona, Iowa E1025130 entity
Predicate hasPark P105 FINISHED
Object Ambrose A. Call State Park
Ambrose A. Call State Park is a small, wooded Iowa state park known for its hiking trails, picnic areas, and historic log cabin near Algona in Kossuth County.
E2144147 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: Ambrose A. Call State Park | Statement: [Algona, Iowa, hasPark, Ambrose A. Call State Park]
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: Ambrose A. Call State Park
Triple: [Algona, Iowa, hasPark, Ambrose A. Call State Park]
Generated description
Ambrose A. Call State Park is a small, wooded Iowa state park known for its hiking trails, picnic areas, and historic log cabin near Algona in Kossuth County.

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_69f76dfa20d0819089585dc2cf653aea completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796abf3b48190a8c759b7166271e8 completed May 3, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a27e5008190a3501feebe23da6f completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384b507d04819089e1652a77293a95 completed June 21, 2026, 8:36 p.m.
NED2 Entity disambiguation (via description) batch_6a384bc4f5fc8190a2e28576b9919d9e completed June 21, 2026, 8:38 p.m.
Created at: May 3, 2026, 4:04 p.m.