Triple

T29376383
Position Surface form Disambiguated ID Type / Status
Subject Hugo de Lantins E745008 entity
Predicate contemporaryOf P6401 FINISHED
Object Arnold de Lantins
Arnold de Lantins was an early 15th-century Franco-Flemish composer known for his sacred and secular vocal music during the late medieval to early Renaissance transition.
E1868347 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: Arnold de Lantins | Statement: [Hugo de Lantins, contemporaryOf, Arnold de Lantins]
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: Arnold de Lantins
Triple: [Hugo de Lantins, contemporaryOf, Arnold de Lantins]
Generated description
Arnold de Lantins was an early 15th-century Franco-Flemish composer known for his sacred and secular vocal music during the late medieval to early Renaissance transition.

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_69f0a79ba954819094597628112c6091 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f669aeb2208190b5b578c5d94edb63 completed May 2, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0fe09908190aacf15594a88f3de completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f6362f6081909a04ef3fbd5bb67f completed June 7, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a25fa9d98d08190aef6fb0a1779f501 completed June 7, 2026, 11:11 p.m.
Created at: April 28, 2026, 2:31 p.m.