Triple

T32857328
Position Surface form Disambiguated ID Type / Status
Subject Clearfield County E840410 entity
Predicate hasMajorHighway P385 FINISHED
Object Pennsylvania Route 879
Pennsylvania Route 879 is a state highway in Pennsylvania that runs through central parts of the state, serving communities in and around Clearfield County.
E2290183 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: Pennsylvania Route 879 | Statement: [Clearfield County, hasMajorHighway, Pennsylvania Route 879]
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: Pennsylvania Route 879
Triple: [Clearfield County, hasMajorHighway, Pennsylvania Route 879]
Generated description
Pennsylvania Route 879 is a state highway in Pennsylvania that runs through central parts of the state, serving communities in and around Clearfield County.

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_69f34942465c819099b3fb47f9044f58 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6ce7fbc948190b155cf930f7962d3 completed May 3, 2026, 4:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5ba6f31f7c81908f30766edc85c556 completed July 18, 2026, 4:16 p.m.
NEDg Description generation batch_6a5ba76c0b9c8190ad977446b1f220cf completed July 18, 2026, 4:18 p.m.
NED2 Entity disambiguation (via description) batch_6a5ba7aa3ec88190b87410583a975809 completed July 18, 2026, 4:19 p.m.
Created at: May 1, 2026, 1:17 a.m.