Triple

T8094932
Position Surface form Disambiguated ID Type / Status
Subject Danilovich E188958 entity
Predicate derivedFromGivenName P17 FINISHED
Object Danilo
Danilo is a masculine given name used in various Slavic and Romance languages, generally equivalent to Daniel and meaning "God is my judge."
 E708994 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: Danilo | Statement: [Danilovich, derivedFromGivenName, Danilo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Danilo
Context triple: [Danilovich, derivedFromGivenName, Danilo]
  • A. Luka
    Luka is a central character in Maxim Gorky's play "The Lower Depths," known as a compassionate wanderer whose comforting lies and philosophical outlook profoundly affect the other destitute inhabitants of the shelter.
  • B. Luka
    Luka is the young protagonist of Salman Rushdie’s fantasy novel "Luka and the Fire of Life," who embarks on a magical quest to save his father.
  • C. Silvano
    Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
  • D. Dario
    Dario is a masculine given name of Italian origin, commonly used in various European and Latin American countries.
  • E. Matija
    Matija is a South Slavic given name, equivalent to the English name Matthew.
  • 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: Danilo
Triple: [Danilovich, derivedFromGivenName, Danilo]
Generated description
Danilo is a masculine given name used in various Slavic and Romance languages, generally equivalent to Daniel and meaning "God is my judge."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Danilo
Target entity description: Danilo is a masculine given name used in various Slavic and Romance languages, generally equivalent to Daniel and meaning "God is my judge."
  • A. Luka
    Luka is a central character in Maxim Gorky's play "The Lower Depths," known as a compassionate wanderer whose comforting lies and philosophical outlook profoundly affect the other destitute inhabitants of the shelter.
  • B. Luka
    Luka is the young protagonist of Salman Rushdie’s fantasy novel "Luka and the Fire of Life," who embarks on a magical quest to save his father.
  • C. Silvano
    Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
  • D. Dario
    Dario is a masculine given name of Italian origin, commonly used in various European and Latin American countries.
  • E. Matija
    Matija is a South Slavic given name, equivalent to the English name Matthew.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc6414ca048190ac0e644b2c399bfb completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc651eecf481909bf0ea90001c83f3 completed April 1, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69cc664d69a08190b92e34a0e1de48a7 completed April 1, 2026, 12:26 a.m.
Created at: March 30, 2026, 5:30 p.m.