Triple

T35145433
Position Surface form Disambiguated ID Type / Status
Subject Conestoga Township, Pennsylvania E1014815 entity
Predicate hasHistoricCommunity P11485 FINISHED
Object Slackwater, Pennsylvania
Slackwater, Pennsylvania is a historic unincorporated community located within Conestoga Township in Lancaster County.
E2127006 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: Slackwater, Pennsylvania | Statement: [Conestoga Township, Pennsylvania, hasHistoricCommunity, Slackwater, 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: Slackwater, Pennsylvania
Triple: [Conestoga Township, Pennsylvania, hasHistoricCommunity, Slackwater, Pennsylvania]
Generated description
Slackwater, Pennsylvania is a historic unincorporated community located within Conestoga Township in Lancaster 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_69f76dda7c108190a2ffd93eb6c341a7 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78cae2b288190b2c1e56a6aa292df completed May 3, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d95e066481908655fccbeb169c1f completed June 21, 2026, 12:30 p.m.
NEDg Description generation batch_6a37da562654819080893c616ec257e2 completed June 21, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_6a37dbed7540819081bd95af5520b163 completed June 21, 2026, 12:41 p.m.
Created at: May 3, 2026, 4:02 p.m.