Triple

T37585731
Position Surface form Disambiguated ID Type / Status
Subject Riva, Maryland E935099 entity
Predicate hasRiverCrossing P1970 FINISHED
Object South River Bridge
South River Bridge is a roadway bridge in Riva, Maryland, that carries traffic across the South River near the western shore of the Chesapeake Bay.
 E2283017 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: South River Bridge | Statement: [Riva, Maryland, hasRiverCrossing, South River 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: South River Bridge
Triple: [Riva, Maryland, hasRiverCrossing, South River Bridge]
Generated description
South River Bridge is a roadway bridge in Riva, Maryland, that carries traffic across the South River near the western shore of the Chesapeake Bay.

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_69f76ece61dc8190a0ab33f8d87d0a7e completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba88dda78819086e76736f0ffa8a7 completed May 6, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a423415858c81908863a964863c4947 completed June 29, 2026, 9 a.m.
NEDg Description generation batch_6a4234ad82b88190bb0461ace7d4f287 completed June 29, 2026, 9:02 a.m.
NED2 Entity disambiguation (via description) batch_6a4238d9ed00819099554623a204958b completed June 29, 2026, 9:20 a.m.
Created at: May 3, 2026, 4:17 p.m.