Triple

T25157684
Position Surface form Disambiguated ID Type / Status
Subject Hendrik Willem van Loon E626359 entity
Predicate spouse P13 FINISHED
Object Elisabeth Sanford
Elisabeth Sanford was the wife of Dutch-American historian and author Hendrik Willem van Loon, known for her connection to his personal and literary life.
E1671908 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: Elisabeth Sanford | Statement: [Hendrik Willem van Loon, spouse, Elisabeth Sanford]
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: Elisabeth Sanford
Triple: [Hendrik Willem van Loon, spouse, Elisabeth Sanford]
Generated description
Elisabeth Sanford was the wife of Dutch-American historian and author Hendrik Willem van Loon, known for her connection to his personal and literary life.

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_69e2ff2834ec8190b0872e2ec3d76023 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f46b8a2dcc81908fc6d9f01dbb2c63 completed May 1, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067c45a2c8190a1d265a67f5e574a completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1068d5ff248190b9efb77366147c26 completed May 22, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1069cb170c8190b31daf74fff26c35 completed May 22, 2026, 2:35 p.m.
Created at: April 18, 2026, 6:30 a.m.