Triple

T3752058
Position Surface form Disambiguated ID Type / Status
Subject Saint Sava E81354 entity
Predicate givenName P17 FINISHED
Object Rastko
Rastko, later known as Saint Sava, was a medieval Serbian prince who became a monk and is revered as the founder of the Serbian Orthodox Church and a key figure in Serbian medieval culture and education.
 E383433 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: Rastko | Statement: [Saint Sava, givenName, Rastko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rastko
Context triple: [Saint Sava, givenName, Rastko]
  • A. Ilija
    Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
  • B. Mihajlo
    Mihajlo is the Serbian given name of Michael I. Pupin, the renowned Serbian-American physicist, inventor, and Columbia University professor.
  • C. Petar
    Petar is a given name commonly used in Slavic countries, equivalent to the English name Peter.
  • D. Preslav
    Preslav is an ancient Bulgarian city that served as a major medieval political and cultural capital of the First Bulgarian Empire and a key center of Slavic literacy and Orthodox Christianity.
  • E. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • 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: Rastko
Triple: [Saint Sava, givenName, Rastko]
Generated description
Rastko, later known as Saint Sava, was a medieval Serbian prince who became a monk and is revered as the founder of the Serbian Orthodox Church and a key figure in Serbian medieval culture and education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rastko
Target entity description: Rastko, later known as Saint Sava, was a medieval Serbian prince who became a monk and is revered as the founder of the Serbian Orthodox Church and a key figure in Serbian medieval culture and education.
  • A. Ilija
    Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
  • B. Mihajlo
    Mihajlo is the Serbian given name of Michael I. Pupin, the renowned Serbian-American physicist, inventor, and Columbia University professor.
  • C. Petar
    Petar is a given name commonly used in Slavic countries, equivalent to the English name Peter.
  • D. Preslav
    Preslav is an ancient Bulgarian city that served as a major medieval political and cultural capital of the First Bulgarian Empire and a key center of Slavic literacy and Orthodox Christianity.
  • E. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb92135c819093f6d616d3ad28ff completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db34aa5c8190ba3f22ee0f1f4208 completed March 14, 2026, 3:51 a.m.
NEDg Description generation batch_69b4dbded2c8819084c26ae2ec1c19b3 completed March 14, 2026, 3:54 a.m.
NED2 Entity disambiguation (via description) batch_69b4dc9cdfc48190be9ff5c501c9efcb completed March 14, 2026, 3:57 a.m.
Created at: March 8, 2026, 3:35 p.m.