Triple

T24527841
Position Surface form Disambiguated ID Type / Status
Subject Isle of Wight Bay E606714 entity
Predicate crossedBy P416 FINISHED
Object Harry W. Kelley Memorial Bridge
The Harry W. Kelley Memorial Bridge is a highway bridge in Ocean City, Maryland, that carries U.S. Route 50 over the water into the resort town’s downtown area.
E1825918 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: Harry W. Kelley Memorial Bridge | Statement: [Isle of Wight Bay, crossedBy, Harry W. Kelley Memorial Bridge]
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: Harry W. Kelley Memorial Bridge
Triple: [Isle of Wight Bay, crossedBy, Harry W. Kelley Memorial Bridge]
Generated description
The Harry W. Kelley Memorial Bridge is a highway bridge in Ocean City, Maryland, that carries U.S. Route 50 over the water into the resort town’s downtown area.

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_69e2c4c85778819085f5da9af3569ad5 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8776d548190a94a2a7b0861e19c completed April 30, 2026, 12:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6af921c8190bf54309547dbe2c0 completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cbb03eb108190b803648e76979f61 completed May 31, 2026, 10:49 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbb6b48388190a59c11c0db620821 completed May 31, 2026, 10:51 p.m.
Created at: April 18, 2026, 2:25 a.m.