Triple

T8402709
Position Surface form Disambiguated ID Type / Status
Subject Bradford County, Pennsylvania E198414 entity
Predicate previousName P65 FINISHED
Object Ontario County, Pennsylvania
Ontario County, Pennsylvania was the former name of what is now known as Bradford County in the Commonwealth of Pennsylvania.
E2282122 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: Ontario County, Pennsylvania | Statement: [Bradford County, Pennsylvania, previousName, Ontario County, Pennsylvania]
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: Ontario County, Pennsylvania
Triple: [Bradford County, Pennsylvania, previousName, Ontario County, Pennsylvania]
Generated description
Ontario County, Pennsylvania was the former name of what is now known as Bradford County in the Commonwealth of Pennsylvania.

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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb824efa5c81908ce816cdb8e1fcfb completed March 31, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a420e0b4b9c81909c9ff25b1e7add74 completed June 29, 2026, 6:17 a.m.
NEDg Description generation batch_6a420ee447e881908e1fc633c8b8a22e completed June 29, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_6a420f5b6f6c81909a2978668cb0c870 completed June 29, 2026, 6:23 a.m.
Created at: March 30, 2026, 6:04 p.m.