Triple

T24919442
Position Surface form Disambiguated ID Type / Status
Subject Lower Alsace Township, Berks County, Pennsylvania E624079 entity
Predicate contains P35 FINISHED
Object Stony Creek
Stony Creek is a waterway in Berks County, Pennsylvania, known locally as a natural feature running through Lower Alsace Township.
E1913436 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: Stony Creek | Statement: [Lower Alsace Township, Berks County, Pennsylvania, contains, Stony Creek]
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: Stony Creek
Triple: [Lower Alsace Township, Berks County, Pennsylvania, contains, Stony Creek]
Generated description
Stony Creek is a waterway in Berks County, Pennsylvania, known locally as a natural feature running through Lower Alsace Township.

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_69e2fac889c081908e9ff686cb428e5a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4238f98ec8190a4159dcec666fe5a completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a278913a82c8190aee83a61e55212ff completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a2789db54048190ab54d623ce1d4e2a completed June 9, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_6a278a76f450819095acd3e2b23d2b73 completed June 9, 2026, 3:37 a.m.
Created at: April 18, 2026, 5:28 a.m.