Triple

T4301045
Position Surface form Disambiguated ID Type / Status
Subject Dagmar E99835 entity
Predicate hasDiminutive P456 FINISHED
Object Dáša
Dáša is a common Czech and Slovak feminine given name, typically used as a diminutive form of Dagmar.
 E428673 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: Dáša | Statement: [Dagmar, hasDiminutive, Dáša]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dáša
Context triple: [Dagmar, hasDiminutive, Dáša]
  • A. Doroteja
    Doroteja is a feminine given name, commonly used in Slavic countries, that is a variant of the name Dorothea.
  • B. Neša
    Neša is the ancient name of the city of Kültepe, a major Bronze Age trading center and early Hittite capital in central Anatolia.
  • C. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • D. Sežana
    Sežana is a town in southwestern Slovenia near the Italian border, known as a regional center of the Karst area and an important transport and trade hub.
  • E. Libuše
    Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
  • 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: Dáša
Triple: [Dagmar, hasDiminutive, Dáša]
Generated description
Dáša is a common Czech and Slovak feminine given name, typically used as a diminutive form of Dagmar.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dáša
Target entity description: Dáša is a common Czech and Slovak feminine given name, typically used as a diminutive form of Dagmar.
  • A. Doroteja
    Doroteja is a feminine given name, commonly used in Slavic countries, that is a variant of the name Dorothea.
  • B. Neša
    Neša is the ancient name of the city of Kültepe, a major Bronze Age trading center and early Hittite capital in central Anatolia.
  • C. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • D. Sežana
    Sežana is a town in southwestern Slovenia near the Italian border, known as a regional center of the Karst area and an important transport and trade hub.
  • E. Libuše
    Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509fb2b88190a13ab88a5b924052 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c74d59688190820cef42c4228a3a completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7bd187c8190b79894c864ea5b19 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c88035dc8190beacf43974a29c78 completed March 14, 2026, 8:43 p.m.
Created at: March 12, 2026, 11:08 p.m.