Triple

T17571371
Position Surface form Disambiguated ID Type / Status
Subject Bryan County, Georgia E427944 entity
Predicate containsTransportationInfrastructure P1298 FINISHED
Object State Route 144
State Route 144 is a state highway in Georgia that serves as a key east–west corridor through Bryan County and surrounding areas.
E2040470 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 144 | Statement: [Bryan County, Georgia, containsTransportationInfrastructure, State Route 144]
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 144
Triple: [Bryan County, Georgia, containsTransportationInfrastructure, State Route 144]
Generated description
State Route 144 is a state highway in Georgia that serves as a key east–west corridor through Bryan County and surrounding areas.

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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45930b0748190b55b95c523c47460 completed April 19, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35259777808190a989f4dc3f43e419 completed June 19, 2026, 11:18 a.m.
NEDg Description generation batch_6a35268520f881909b265b5ea58f2b9b completed June 19, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_6a3529902ecc8190837433ab0a0f7348 completed June 19, 2026, 11:35 a.m.
Created at: April 10, 2026, 5:50 a.m.