Triple

T28082608
Position Surface form Disambiguated ID Type / Status
Subject Anne Whittle E709725 entity
Predicate employer P7 FINISHED
Object Robert Nutter
Robert Nutter was an English Catholic priest and martyr executed in the late 16th century for his religious activities under Elizabeth I.
E1803905 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: Robert Nutter | Statement: [Anne Whittle, employer, Robert Nutter]
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: Robert Nutter
Triple: [Anne Whittle, employer, Robert Nutter]
Generated description
Robert Nutter was an English Catholic priest and martyr executed in the late 16th century for his religious activities under Elizabeth I.

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_69ef9b7037f0819095bb90eaccbcaf32 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f64045bc2c8190b847de0b6c11a6e3 completed May 2, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c91904e8819086256f02136ebef7 completed May 26, 2026, 4:23 p.m.
NEDg Description generation batch_6a15ca0309908190b067af60dc77238a completed May 26, 2026, 4:27 p.m.
NED2 Entity disambiguation (via description) batch_6a15caa74e9c8190ad43be1d8ed6ad15 completed May 26, 2026, 4:30 p.m.
Created at: April 27, 2026, 8:53 p.m.