Triple

T37173806
Position Surface form Disambiguated ID Type / Status
Subject Juhani Aho E920984 entity
Predicate birthName P65 FINISHED
Object Johannes Brofeldt
Johannes Brofeldt, better known by his pen name Juhani Aho, was a prominent Finnish author and journalist regarded as one of the pioneers of modern Finnish literature.
E2283937 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: Johannes Brofeldt | Statement: [Juhani Aho, birthName, Johannes Brofeldt]
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: Johannes Brofeldt
Triple: [Juhani Aho, birthName, Johannes Brofeldt]
Generated description
Johannes Brofeldt, better known by his pen name Juhani Aho, was a prominent Finnish author and journalist regarded as one of the pioneers of modern Finnish literature.

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_69f76ea16f288190b445aa1604d996f4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb35eb5dc48190abdf5eea9b351298 completed May 6, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a43093e3d7c81908de149ad38ccf83f completed June 30, 2026, 12:09 a.m.
NEDg Description generation batch_6a430b82ab288190aff1422e4c8d0c96 completed June 30, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a430ccc9108819083a39f2b5b01ea1c completed June 30, 2026, 12:24 a.m.
Created at: May 3, 2026, 4:15 p.m.