Triple

T25765815
Position Surface form Disambiguated ID Type / Status
Subject Redmond Central Connector E648879 entity
Predicate connectsTo P845 FINISHED
Object Redmond Downtown Park
Redmond Downtown Park is a central urban green space in Redmond, Washington, featuring open lawns, community gathering areas, and recreational amenities in the heart of the city’s downtown.
E1698559 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: Redmond Downtown Park | Statement: [Redmond Central Connector, connectsTo, Redmond Downtown 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: Redmond Downtown Park
Triple: [Redmond Central Connector, connectsTo, Redmond Downtown Park]
Generated description
Redmond Downtown Park is a central urban green space in Redmond, Washington, featuring open lawns, community gathering areas, and recreational amenities in the heart of the city’s downtown.

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_69e7ab322db0819092d6a2b3d4572e01 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fdf2b7f48190bc8fdef839e9d005 completed May 2, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da0a82bc819080d638038e17d537 completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10dbf4dd848190b6ae5aefecf04278 completed May 22, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a10dc7a3a50819089ed854ac6463fe6 completed May 22, 2026, 10:45 p.m.
Created at: April 22, 2026, 5:10 a.m.