Triple

T33656543
Position Surface form Disambiguated ID Type / Status
Subject William Thornton E862234 entity
Predicate spouse P13 FINISHED
Object Anna Maria Thornton
Anna Maria Thornton was a prominent early 19th-century Washington, D.C. socialite and diarist, known for her detailed journals documenting political and social life in the young United States.
E2060762 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: Anna Maria Thornton | Statement: [William Thornton, spouse, Anna Maria Thornton]
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: Anna Maria Thornton
Triple: [William Thornton, spouse, Anna Maria Thornton]
Generated description
Anna Maria Thornton was a prominent early 19th-century Washington, D.C. socialite and diarist, known for her detailed journals documenting political and social life in the young United States.

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_69f349840ba881908e3bfce536aeb92b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f9edbfc4819099e45e8ffa57f8db completed May 3, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a362723cc8081909afb66da4176078d completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3627bba8bc81909091699b621fd31b completed June 20, 2026, 5:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3628683bac81908b766d3154f2188d completed June 20, 2026, 5:43 a.m.
Created at: May 1, 2026, 1:42 a.m.