Triple

T24557044
Position Surface form Disambiguated ID Type / Status
Subject Howland Township E607543 entity
Predicate hasMajorRoad P385 FINISHED
Object State Route 82
State Route 82 is a significant east–west state highway in Ohio that serves as a major transportation corridor through several communities, including Howland Township.
 E2291084 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: State Route 82 | Statement: [Howland Township, hasMajorRoad, State Route 82]
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: State Route 82
Triple: [Howland Township, hasMajorRoad, State Route 82]
Generated description
State Route 82 is a significant east–west state highway in Ohio that serves as a major transportation corridor through several communities, including Howland Township.

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_69e2c4cae1b88190825e88d5ce8aa61e completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8f2af7c8190904f247ef29121d0 completed April 30, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c23773ff48190b23987de25744901 completed July 19, 2026, 1:08 a.m.
NEDg Description generation batch_6a5c241ab91881908b98987857396778 completed July 19, 2026, 1:10 a.m.
NED2 Entity disambiguation (via description) batch_6a5c24699574819099a30ee89ee6bad7 completed July 19, 2026, 1:12 a.m.
Created at: April 18, 2026, 2:27 a.m.