Triple

T21831444
Position Surface form Disambiguated ID Type / Status
Subject Mississippi Highway 21 E539003 entity
Predicate passesThrough P225 FINISHED
Object Sebastopol, Mississippi
Sebastopol, Mississippi is a small rural town in central Mississippi known for its agricultural surroundings and location along key state highways.
 E822801 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: Sebastopol, Mississippi | Statement: [Mississippi Highway 21, passesThrough, Sebastopol, Mississippi]
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: Sebastopol, Mississippi
Triple: [Mississippi Highway 21, passesThrough, Sebastopol, Mississippi]
Generated description
Sebastopol, Mississippi is a small rural town in central Mississippi known for its agricultural surroundings and location along key state highways.

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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f091362d9081909f00ad7a2806d5cb completed April 28, 2026, 10:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c0fa870c81909ae631e459d1737f completed May 22, 2026, 8:47 p.m.
NEDg Description generation batch_6a10c2d522988190bc01978dc5ef272f completed May 22, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a10c365b12c8190bc9b683ad855c776 completed May 22, 2026, 8:58 p.m.
Created at: April 16, 2026, 6:55 p.m.