Triple

T11243477
Position Surface form Disambiguated ID Type / Status
Subject Lennart E266135 entity
Predicate etymologicalRoot P453 FINISHED
Object Leonardus
Leonardus is a Latin given name of Germanic origin that underlies later forms such as Lennart and Leonard.
 E913538 NE FINISHED

How this triple was built (4 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: Leonardus | Statement: [Lennart, etymologicalRoot, Leonardus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leonardus
Context triple: [Lennart, etymologicalRoot, Leonardus]
  • A. Lambertus
    Lambertus is a Latinized given name historically used in European contexts, particularly in religious and scholarly settings.
  • B. Leodore
    Leodore is the first name of Mayor Lionheart, the lion politician who serves as the mayor of Zootopia in Disney's animated film "Zootopia."
  • C. Nicolaus
    Nicolaus is a small unincorporated community in Sutter County, California, located near the Feather River in the Sacramento Valley.
  • D. Nicolaus
    Nicolaus is a Latin given name of Greek origin, historically borne by various religious figures, scholars, and notable individuals across Europe.
  • E. Laurentius
    Laurentius is a Latin given name historically borne by several early Christian saints and later adapted into various European forms such as Laurence and Lawrence.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Leonardus
Triple: [Lennart, etymologicalRoot, Leonardus]
Generated description
Leonardus is a Latin given name of Germanic origin that underlies later forms such as Lennart and Leonard.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leonardus
Target entity description: Leonardus is a Latin given name of Germanic origin that underlies later forms such as Lennart and Leonard.
  • A. Lambertus
    Lambertus is a Latinized given name historically used in European contexts, particularly in religious and scholarly settings.
  • B. Leodore
    Leodore is the first name of Mayor Lionheart, the lion politician who serves as the mayor of Zootopia in Disney's animated film "Zootopia."
  • C. Nicolaus
    Nicolaus is a small unincorporated community in Sutter County, California, located near the Feather River in the Sacramento Valley.
  • D. Nicolaus
    Nicolaus is a Latin given name of Greek origin, historically borne by various religious figures, scholars, and notable individuals across Europe.
  • E. Laurentius
    Laurentius is a Latin given name historically borne by several early Christian saints and later adapted into various European forms such as Laurence and Lawrence.
  • F. None of above. chosen

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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91b0b808190bc38008bb344d180 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad849f70819098a7056fbc4831ff completed April 19, 2026, 10:25 a.m.
NEDg Description generation batch_69e4b12eee348190bee6c84587e4955d completed April 19, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_69e4be2bb8c88190a21773b0c43b6b99 completed April 19, 2026, 11:36 a.m.
Created at: April 8, 2026, 9:30 p.m.