Triple

T32392646
Position Surface form Disambiguated ID Type / Status
Subject Malcolm H. Kerr E827714 entity
Predicate spouse P13 FINISHED
Object Ann Zwicker Kerr
Ann Zwicker Kerr is an American author and academic administrator known for her work in international education and for preserving the legacy of her late husband, Middle East scholar Malcolm H. Kerr.
 E2004518 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: Ann Zwicker Kerr | Statement: [Malcolm H. Kerr, spouse, Ann Zwicker Kerr]
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: Ann Zwicker Kerr
Triple: [Malcolm H. Kerr, spouse, Ann Zwicker Kerr]
Generated description
Ann Zwicker Kerr is an American author and academic administrator known for her work in international education and for preserving the legacy of her late husband, Middle East scholar Malcolm H. Kerr.

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_69f349184e7481909c6c54428cb9cf12 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c20f209081909fb9ac8f95069f04 completed May 3, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a33e8c27dcc8190808f1f28950f5a90 completed June 18, 2026, 12:46 p.m.
NEDg Description generation batch_6a33ea4cfff481908a971944094905b5 completed June 18, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_6a3441771ec08190b5d275561176850c completed June 18, 2026, 7:05 p.m.
Created at: May 1, 2026, 12:52 a.m.