Triple

T27358068
Position Surface form Disambiguated ID Type / Status
Subject Walnut Grove, Missouri E685740 entity
Predicate roadAccess P385 FINISHED
Object Missouri Route 123
Missouri Route 123 is a state highway in southwestern Missouri that connects several rural communities and provides regional access to larger routes.
 E1819386 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: Missouri Route 123 | Statement: [Walnut Grove, Missouri, roadAccess, Missouri Route 123]
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: Missouri Route 123
Triple: [Walnut Grove, Missouri, roadAccess, Missouri Route 123]
Generated description
Missouri Route 123 is a state highway in southwestern Missouri that connects several rural communities and provides regional access to larger routes.

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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62c20321481908ba574ad96d93013 completed May 2, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16415670348190a1894d6204f72a1d completed May 27, 2026, 12:56 a.m.
NEDg Description generation batch_6a16428c40688190a86a99c8c936de3e completed May 27, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a164322f1148190b37794a5fc54f184 completed May 27, 2026, 1:04 a.m.
Created at: April 27, 2026, 11:52 a.m.