Triple

T26914101
Position Surface form Disambiguated ID Type / Status
Subject Waynesboro, Mississippi E677468 entity
Predicate isServedByHighway P385 FINISHED
Object Mississippi Highway 63
Mississippi Highway 63 is a state highway in Mississippi that runs through the southeastern part of the state, connecting several communities and serving as a regional transportation route.
 E1828620 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: Mississippi Highway 63 | Statement: [Waynesboro, Mississippi, isServedByHighway, Mississippi Highway 63]
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: Mississippi Highway 63
Triple: [Waynesboro, Mississippi, isServedByHighway, Mississippi Highway 63]
Generated description
Mississippi Highway 63 is a state highway in Mississippi that runs through the southeastern part of the state, connecting several communities and serving as a regional transportation route.

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_69eee9bcef1c8190be88586bb902bb9b completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fdc239c81908b7bebeb2d8a8a20 completed May 2, 2026, 4:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc350bf0c819081c0326c83b97914 completed May 31, 2026, 11:25 p.m.
NEDg Description generation batch_6a1cc44ac1448190b0dc305eb5e460be completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc571b3b481908c523e5bad5e086a completed May 31, 2026, 11:34 p.m.
Created at: April 27, 2026, 6:03 a.m.