Triple

T32529718
Position Surface form Disambiguated ID Type / Status
Subject Missouri River bridges E831415 entity
Predicate hasNotableExample P1259 FINISHED
Object Grant Marsh Bridge
The Grant Marsh Bridge is a major vehicular bridge in North Dakota that carries Interstate 94 across the Missouri River near Bismarck.
E2133088 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: Grant Marsh Bridge | Statement: [Missouri River bridges, hasNotableExample, Grant Marsh 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: Grant Marsh Bridge
Triple: [Missouri River bridges, hasNotableExample, Grant Marsh Bridge]
Generated description
The Grant Marsh Bridge is a major vehicular bridge in North Dakota that carries Interstate 94 across the Missouri River near Bismarck.

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_69f34924b1cc8190ad3aca0c0f012a7e completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c51ba4248190b98f43a5866bab0d completed May 3, 2026, 3:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a380f8161708190a47f70dccdd9155f completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a3810a299448190ba0080197e6417de completed June 21, 2026, 4:26 p.m.
NED2 Entity disambiguation (via description) batch_6a3811ab6ed8819097a93f8022d9d284 completed June 21, 2026, 4:30 p.m.
Created at: May 1, 2026, 1:01 a.m.