Triple

T8342235
Position Surface form Disambiguated ID Type / Status
Subject Therese E195946 entity
Predicate relatedName P3889 FINISHED
Object Tereza
Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
 E728423 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: Tereza | Statement: [Therese, relatedName, Tereza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tereza
Context triple: [Therese, relatedName, Tereza]
  • A. Tereza Vávrová
    Tereza Vávrová is a notable bearer of the Czech surname Vávrová, recognized enough to be specifically cited in reference to the name.
  • B. Antónia
    Antónia is a feminine given name commonly used in various European languages, often as a variant of Antonia.
  • C. Helena Davidová
    Helena Davidová is a member of Franz Kafka’s extended family, known as the daughter of his sister Ottla Kafka.
  • D. Milena
    Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
  • E. Mária
    Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
  • 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: Tereza
Triple: [Therese, relatedName, Tereza]
Generated description
Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tereza
Target entity description: Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
  • A. Tereza Vávrová
    Tereza Vávrová is a notable bearer of the Czech surname Vávrová, recognized enough to be specifically cited in reference to the name.
  • B. Antónia
    Antónia is a feminine given name commonly used in various European languages, often as a variant of Antonia.
  • C. Helena Davidová
    Helena Davidová is a member of Franz Kafka’s extended family, known as the daughter of his sister Ottla Kafka.
  • D. Milena
    Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
  • E. Mária
    Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fe9efec81908e0c9ded3963bac5 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc72bc43c81909d95c7eb6aefc403 completed April 2, 2026, 1:32 a.m.
NEDg Description generation batch_69cdcb90bec88190a2c19681405aa13e completed April 2, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69cdcd0fc9488190a0a576c385b9bc1f completed April 2, 2026, 1:57 a.m.
Created at: March 30, 2026, 5:58 p.m.