Triple

T9284081
Position Surface form Disambiguated ID Type / Status
Subject Martin E223140 entity
Predicate hasCognate P2525 FINISHED
Object Mártinus
Mártinus is a Latin given name from which the modern name Martin is derived, historically associated with Saint Martin of Tours and widely used across Europe.
 E789313 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: Mártinus | Statement: [Martin, hasCognate, Mártinus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mártinus
Context triple: [Martin, hasCognate, Mártinus]
  • A. Marianus
    Marianus is a Latin personal name, historically used in the Roman world and later in various European cultures, derived from the root name Marian.
  • B. Melchior
    Melchior is traditionally known as one of the Three Wise Men or Magi who visited the infant Jesus, often depicted as an aged king bearing gifts.
  • C. Marcellino
    Marcellino is an Italian given name, typically used as a diminutive or affectionate form of Marcello.
  • D. Aloysius
    Aloysius is a masculine given name of Latinized form, historically borne by several saints and used in various European languages.
  • E. Petrus
    Petrus is the Latin form of the name Peter, historically used in religious and classical contexts and serving as the root for various European given names.
  • 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: Mártinus
Triple: [Martin, hasCognate, Mártinus]
Generated description
Mártinus is a Latin given name from which the modern name Martin is derived, historically associated with Saint Martin of Tours and widely used across Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mártinus
Target entity description: Mártinus is a Latin given name from which the modern name Martin is derived, historically associated with Saint Martin of Tours and widely used across Europe.
  • A. Marianus
    Marianus is a Latin personal name, historically used in the Roman world and later in various European cultures, derived from the root name Marian.
  • B. Melchior
    Melchior is traditionally known as one of the Three Wise Men or Magi who visited the infant Jesus, often depicted as an aged king bearing gifts.
  • C. Marcellino
    Marcellino is an Italian given name, typically used as a diminutive or affectionate form of Marcello.
  • D. Aloysius
    Aloysius is a masculine given name of Latinized form, historically borne by several saints and used in various European languages.
  • E. Petrus
    Petrus is the Latin form of the name Peter, historically used in religious and classical contexts and serving as the root for various European given names.
  • 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_69ca842123588190b3f2e1a69037d141 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd081e72988190917f425e64631837 completed April 1, 2026, 11:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b21d8f1081909b2493151fde4a5f completed April 4, 2026, 6:39 a.m.
NEDg Description generation batch_69d0b3234d088190a8ed13b4d4772fb5 completed April 4, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_69d0b3bcd5548190ba1af3d0fa72780a completed April 4, 2026, 6:46 a.m.
Created at: March 30, 2026, 7:34 p.m.