Triple

T31656989
Position Surface form Disambiguated ID Type / Status
Subject Miller Symphony Hall E807882 entity
Predicate partOf P40 FINISHED
Object Old Allentown Historic District
Old Allentown Historic District is a historic neighborhood in Allentown, Pennsylvania, known for its preserved 19th- and early 20th-century architecture and cultural landmarks.
E1971729 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: Old Allentown Historic District | Statement: [Miller Symphony Hall, partOf, Old Allentown Historic District]
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: Old Allentown Historic District
Triple: [Miller Symphony Hall, partOf, Old Allentown Historic District]
Generated description
Old Allentown Historic District is a historic neighborhood in Allentown, Pennsylvania, known for its preserved 19th- and early 20th-century architecture and cultural landmarks.

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_69f348daf95c81908b4c985b7ddcd0b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a95f453081908414920057d97c90 completed May 3, 2026, 1:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79e926b08190a95beab4c930d24f completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a6983e481908c22bc6844ca0bd2 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b71012c81909354fe000b507fc9 completed June 12, 2026, 3:22 a.m.
Created at: April 30, 2026, 10:55 p.m.