Triple

T35769842
Position Surface form Disambiguated ID Type / Status
Subject Mount Carmel Cemetery E1034128 entity
Predicate hasNotableBurial P196 FINISHED
Object Bishop Raymond P. Hillinger
Bishop Raymond P. Hillinger was a Roman Catholic prelate who served as an auxiliary bishop of the Archdiocese of Chicago in the mid-20th century.
E2194869 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: Bishop Raymond P. Hillinger | Statement: [Mount Carmel Cemetery, hasNotableBurial, Bishop Raymond P. Hillinger]
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: Bishop Raymond P. Hillinger
Triple: [Mount Carmel Cemetery, hasNotableBurial, Bishop Raymond P. Hillinger]
Generated description
Bishop Raymond P. Hillinger was a Roman Catholic prelate who served as an auxiliary bishop of the Archdiocese of Chicago in the mid-20th century.

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_69f76e13edd081909101629aa829c4ad completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1f64f1081908cc2774840684310 completed May 3, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20aae188819093007ca7be8ce211 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a2108705081908bc39b9bba5c71bf completed June 23, 2026, 6 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3390427081909ddf30ecbcf6ab72 completed June 23, 2026, 7:19 a.m.
Created at: May 3, 2026, 4:06 p.m.