Triple

T1147343
Position Surface form Disambiguated ID Type / Status
Subject Dana Vávrová E23595 entity
Predicate givenName P17 FINISHED
Object Dana
Dana is a feminine given name commonly used in various cultures, including Czech, English, and Hebrew-speaking communities.
 E135363 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: Dana | Statement: [Dana Vávrová, givenName, Dana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dana
Context triple: [Dana Vávrová, givenName, Dana]
  • A. Dana
    Dana is a scientific work or authority that provides the formal description and classification of Antarctic krill.
  • B. Osnos
    Osnos is a surname most notably associated with American journalist and author Peter Osnos and his family.
  • C. Trent
    The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
  • D. Cana
    Cana is a small town in the region of Galilee, traditionally known in Christian tradition as the site where Jesus performed his first miracle of turning water into wine.
  • E. Dina
    Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
  • 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: Dana
Triple: [Dana Vávrová, givenName, Dana]
Generated description
Dana is a feminine given name commonly used in various cultures, including Czech, English, and Hebrew-speaking communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dana
Target entity description: Dana is a feminine given name commonly used in various cultures, including Czech, English, and Hebrew-speaking communities.
  • A. Dana
    Dana is a scientific work or authority that provides the formal description and classification of Antarctic krill.
  • B. Osnos
    Osnos is a surname most notably associated with American journalist and author Peter Osnos and his family.
  • C. Trent
    The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
  • D. Cana
    Cana is a small town in the region of Galilee, traditionally known in Christian tradition as the site where Jesus performed his first miracle of turning water into wine.
  • E. Dina
    Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc7041248190893e4c655dbd0604 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f139a008190a20f38330364dd2b completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac7074e7dc81909fbb68c146bbae0a completed March 7, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69ac70c76c2c8190bfb88293645c659e completed March 7, 2026, 6:39 p.m.
Created at: March 1, 2026, 7:44 p.m.