Triple

T27336148
Position Surface form Disambiguated ID Type / Status
Subject Manheim, Pennsylvania E689955 entity
Predicate foundedBy P104 FINISHED
Object Henry William Stiegel
Henry William Stiegel was an 18th-century German-American glassmaker and ironmaster known for his decorative glassware and for developing industrial enterprises in colonial Pennsylvania.
 E1904062 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: Henry William Stiegel | Statement: [Manheim, Pennsylvania, foundedBy, Henry William Stiegel]
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: Henry William Stiegel
Triple: [Manheim, Pennsylvania, foundedBy, Henry William Stiegel]
Generated description
Henry William Stiegel was an 18th-century German-American glassmaker and ironmaster known for his decorative glassware and for developing industrial enterprises in colonial 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_69ef355e5b388190a8fc1eba9b4a6656 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62acf2cdc8190bf8f6954dfd648fe completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2757d0608c8190b83041225ecf0749 completed June 9, 2026, 12:01 a.m.
NEDg Description generation batch_6a275a7d33848190ba11aeb45c7e8b83 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b11987081908ec648ce1eeceed3 completed June 9, 2026, 12:15 a.m.
Created at: April 27, 2026, 11:40 a.m.