Triple

T26626658
Position Surface form Disambiguated ID Type / Status
Subject U.S. Route 309 E668367 entity
Predicate successor P78 FINISHED
Object PA 309
PA 309 is a Pennsylvania state highway that largely follows the former alignment of U.S. Route 309, running through the eastern part of the state and serving as a major regional north–south route.
 E1735026 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: PA 309 | Statement: [U.S. Route 309, successor, PA 309]
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: PA 309
Triple: [U.S. Route 309, successor, PA 309]
Generated description
PA 309 is a Pennsylvania state highway that largely follows the former alignment of U.S. Route 309, running through the eastern part of the state and serving as a major regional north–south 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_69ee9cff507c819092b95bf7219a702e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615ea59048190880a13cb9a9f8126 completed May 2, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec343ae48190860511c4d420194f completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11eda28c48819098126d5c8d74adff completed May 23, 2026, 6:10 p.m.
NED2 Entity disambiguation (via description) batch_6a11ee308af88190b08944270a2fd1d8 completed May 23, 2026, 6:13 p.m.
Created at: April 27, 2026, 2:23 a.m.