Triple

T36903642
Position Surface form Disambiguated ID Type / Status
Subject Rockefeller Township, Pennsylvania E912108 entity
Predicate subdivisionName P747 FINISHED
Object Rockefeller Township
Rockefeller Township is a rural township located in Northumberland County, Pennsylvania, known for its small population and predominantly agricultural landscape.
E2202264 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: Rockefeller Township | Statement: [Rockefeller Township, Pennsylvania, subdivisionName, Rockefeller Township]
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: Rockefeller Township
Triple: [Rockefeller Township, Pennsylvania, subdivisionName, Rockefeller Township]
Generated description
Rockefeller Township is a rural township located in Northumberland County, Pennsylvania, known for its small population and predominantly agricultural landscape.

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_69f76e841b54819097e7fa768bbc70b2 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fda79b4c8190927740258cd7388b completed May 5, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfafdc3c0819090ba63442d103fc2 completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3dfd5aa9788190af71bb5c6a7af107 completed June 26, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3e02af021481908d97618a61ce8d54 completed June 26, 2026, 4:40 a.m.
Created at: May 3, 2026, 4:13 p.m.