Triple

T27680601
Position Surface form Disambiguated ID Type / Status
Subject Eastern Idaho E697896 entity
Predicate contains P35 FINISHED
Object Island Park
Island Park is a small resort city in eastern Idaho known for its unusually long, narrow city limits and proximity to outdoor attractions like Yellowstone National Park and Henrys Lake.
E1783321 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: Island Park | Statement: [Eastern Idaho, contains, Island 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: Island Park
Triple: [Eastern Idaho, contains, Island Park]
Generated description
Island Park is a small resort city in eastern Idaho known for its unusually long, narrow city limits and proximity to outdoor attractions like Yellowstone National Park and Henrys 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_69ef590d458c81909583290c3cd0478b completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635383864819095574ddc05b9a51f completed May 2, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12daadb7e48190a6f75b1f7ea098ec completed May 24, 2026, 11:02 a.m.
NEDg Description generation batch_6a12db5d2878819094252a665596a86e completed May 24, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_6a12dbe4c9e4819084be4a4f5e3b58a6 completed May 24, 2026, 11:07 a.m.
Created at: April 27, 2026, 2:46 p.m.