Triple

T21924364
Position Surface form Disambiguated ID Type / Status
Subject Bridgeport Covered Bridge E541402 entity
Predicate hasAlternativeName P39 FINISHED
Object Bridgeport Bridge
Bridgeport Bridge is a historic 19th-century covered wooden bridge in California, renowned as one of the longest single-span covered bridges in the United States.
E1610131 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: Bridgeport Bridge | Statement: [Bridgeport Covered Bridge, hasAlternativeName, Bridgeport 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: Bridgeport Bridge
Triple: [Bridgeport Covered Bridge, hasAlternativeName, Bridgeport Bridge]
Generated description
Bridgeport Bridge is a historic 19th-century covered wooden bridge in California, renowned as one of the longest single-span covered bridges in the United States.

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_69e0c47d74488190a15119108794a307 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1233dc504819083ee27e253805189 completed April 28, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75df2518819085c5f0dc001de791 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f76f167d08190a9e4d3abc3cc4545 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78c015108190bb84972406f84239 completed May 21, 2026, 9:27 p.m.
Created at: April 16, 2026, 7:45 p.m.