Triple

T37621289
Position Surface form Disambiguated ID Type / Status
Subject Bishop Stang High School E936073 entity
Predicate namedAfter P63 FINISHED
Object Bishop James J. Gerrard
Bishop James J. Gerrard was a Roman Catholic prelate from Massachusetts who served as an auxiliary bishop of the Diocese of Fall River in the mid-20th century.
E2242910 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 James J. Gerrard | Statement: [Bishop Stang High School, namedAfter, Bishop James J. Gerrard]
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 James J. Gerrard
Triple: [Bishop Stang High School, namedAfter, Bishop James J. Gerrard]
Generated description
Bishop James J. Gerrard was a Roman Catholic prelate from Massachusetts who served as an auxiliary bishop of the Diocese of Fall River 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_69f76ed16b748190ad6add183b1be688 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba93331348190ac0c18ab4e0d7242 completed May 6, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40f169af248190858fbbff7ddd3f55 completed June 28, 2026, 10:03 a.m.
NEDg Description generation batch_6a40f1d7c538819095daeb9ad4299855 completed June 28, 2026, 10:05 a.m.
NED2 Entity disambiguation (via description) batch_6a40f2aa79808190a3952e3cade199a1 completed June 28, 2026, 10:08 a.m.
Created at: May 3, 2026, 4:18 p.m.