Triple

T10846326
Position Surface form Disambiguated ID Type / Status
Subject Azaria Paz E256017 entity
Predicate givenName P17 FINISHED
Object Azaria
Azaria is a given name used by various individuals, including the Israeli engineer and academic Azaria Paz.
E889660 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: Azaria | Statement: [Azaria Paz, givenName, Azaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azaria
Context triple: [Azaria Paz, givenName, Azaria]
  • A. Tamar
    Tamar is a biblical figure in the Book of 2 Samuel, known as the daughter of King David whose tragic story of abuse and injustice profoundly impacts David’s family narrative.
  • B. Tamar
    "Tamar" is the self-titled debut studio album by American R&B singer Tamar Braxton, showcasing her early solo artistry and vocal style.
  • C. Juliane
    Juliane is a feminine given name, commonly used in various European languages, that is related to and often considered a variant of the name Juliana or Julie.
  • D. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • E. Aliza
    Aliza is a feminine given name, often considered a variant of Eliza and used in various cultures with meanings related to joy or nobility.
  • 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: Azaria
Triple: [Azaria Paz, givenName, Azaria]
Generated description
Azaria is a given name used by various individuals, including the Israeli engineer and academic Azaria Paz.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Azaria
Target entity description: Azaria is a given name used by various individuals, including the Israeli engineer and academic Azaria Paz.
  • A. Tamar
    Tamar is a biblical figure in the Book of 2 Samuel, known as the daughter of King David whose tragic story of abuse and injustice profoundly impacts David’s family narrative.
  • B. Tamar
    "Tamar" is the self-titled debut studio album by American R&B singer Tamar Braxton, showcasing her early solo artistry and vocal style.
  • C. Juliane
    Juliane is a feminine given name, commonly used in various European languages, that is related to and often considered a variant of the name Juliana or Julie.
  • D. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • E. Aliza
    Aliza is a feminine given name, often considered a variant of Eliza and used in various cultures with meanings related to joy or nobility.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d750d132e081909c977b3dc4110ca4 completed April 9, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb162d718819081fbc3a082672b4f completed April 14, 2026, 9:28 p.m.
NEDg Description generation batch_69dec255abb08190bf93573c41aa35e9 completed April 14, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69dec7c48c3c81909365b901830f0906 completed April 14, 2026, 11:03 p.m.
Created at: April 8, 2026, 9:20 p.m.