Triple

T24915808
Position Surface form Disambiguated ID Type / Status
Subject Hermann Grimm E623978 entity
Predicate spouse P13 FINISHED
Object Gisela von Arnim
Gisela von Arnim was a 19th-century German writer and salonnière associated with the Romantic literary circle and the daughter of prominent Romantic authors Bettina and Achim von Arnim.
 E1657059 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: Gisela von Arnim | Statement: [Hermann Grimm, spouse, Gisela von Arnim]
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: Gisela von Arnim
Triple: [Hermann Grimm, spouse, Gisela von Arnim]
Generated description
Gisela von Arnim was a 19th-century German writer and salonnière associated with the Romantic literary circle and the daughter of prominent Romantic authors Bettina and Achim von Arnim.

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_69e2fac889c081908e9ff686cb428e5a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4238c52488190a58b1191f4dc3373 completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10332e5ae481908d0a2236eb137716 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a1033edb6848190b35070d8784af90e completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a103487a09c81908960296ff597228f completed May 22, 2026, 10:48 a.m.
Created at: April 18, 2026, 5:28 a.m.