Triple

T12882178
Position Surface form Disambiguated ID Type / Status
Subject Jackson, MS Metropolitan Statistical Area E308123 entity
Predicate majorHighway P385 FINISHED
Object U.S. Route 51
U.S. Route 51 is a major north–south United States highway that runs from Louisiana to Wisconsin, connecting numerous cities and regions across the central part of the country.
E2286162 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: U.S. Route 51 | Statement: [Jackson, MS Metropolitan Statistical Area, majorHighway, U.S. Route 51]
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: U.S. Route 51
Triple: [Jackson, MS Metropolitan Statistical Area, majorHighway, U.S. Route 51]
Generated description
U.S. Route 51 is a major north–south United States highway that runs from Louisiana to Wisconsin, connecting numerous cities and regions across the central part of the country.

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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fd15888190baf90fc30f2a3e25 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4653bfd96c8190997a165ec9984553 completed July 2, 2026, 12:04 p.m.
NEDg Description generation batch_6a4654a243108190b0f34f9559f96c70 completed July 2, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_6a46553555348190b49361f684c4ea83 completed July 2, 2026, 12:10 p.m.
Created at: April 9, 2026, 5:39 p.m.