Triple

T25162649
Position Surface form Disambiguated ID Type / Status
Subject University Bridge E626481 entity
Predicate hasAlternativeName P39 FINISHED
Object University Bridge (Seattle)
University Bridge (Seattle) is a bascule drawbridge in Seattle, Washington, that carries motor vehicles, cyclists, and pedestrians across the Lake Union Ship Canal between the University District and Eastlake.
E1665751 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: University Bridge (Seattle) | Statement: [University Bridge, hasAlternativeName, University Bridge (Seattle)]
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: University Bridge (Seattle)
Triple: [University Bridge, hasAlternativeName, University Bridge (Seattle)]
Generated description
University Bridge (Seattle) is a bascule drawbridge in Seattle, Washington, that carries motor vehicles, cyclists, and pedestrians across the Lake Union Ship Canal between the University District and Eastlake.

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_69e2ff2834ec8190b0872e2ec3d76023 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f46d3f35848190b56a4373c97a7d64 completed May 1, 2026, 9:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d123bf48190a1e3c96a8d534a08 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105dd1e43c8190b10f80fbfa0d1b87 completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105e720558819080a749cd92cd6fc9 completed May 22, 2026, 1:47 p.m.
Created at: April 18, 2026, 6:31 a.m.