Triple

T7268419
Position Surface form Disambiguated ID Type / Status
Subject Anna E161036 entity
Predicate hasRelatedName P3889 FINISHED
Object Anja
Anja is a feminine given name commonly used in various European countries, often considered a variant of Anna.
 E657515 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: Anja | Statement: [Anna, hasRelatedName, Anja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anja
Context triple: [Anna, hasRelatedName, Anja]
  • A. Anela
    Anela is a small town and comune in the historical Logudoro region of northern Sardinia, Italy.
  • B. Anika
    Anika is the first name of Anika Noni Rose, an American actress and singer best known for voicing Tiana in Disney’s "The Princess and the Frog."
  • C. Katja
    Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European languages.
  • D. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • E. Senta
    Senta is a town in northern Serbia, on the Tisa River, historically notable as the site of the 1697 Battle of Zenta between the Habsburg and Ottoman Empires.
  • 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: Anja
Triple: [Anna, hasRelatedName, Anja]
Generated description
Anja is a feminine given name commonly used in various European countries, often considered a variant of Anna.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anja
Target entity description: Anja is a feminine given name commonly used in various European countries, often considered a variant of Anna.
  • A. Anela
    Anela is a small town and comune in the historical Logudoro region of northern Sardinia, Italy.
  • B. Anika
    Anika is the first name of Anika Noni Rose, an American actress and singer best known for voicing Tiana in Disney’s "The Princess and the Frog."
  • C. Katja
    Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European languages.
  • D. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • E. Senta
    Senta is a town in northern Serbia, on the Tisa River, historically notable as the site of the 1697 Battle of Zenta between the Habsburg and Ottoman Empires.
  • 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae8cc288190bc3ae3c7b38980d0 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eed8c5448190b83faee62f8122de completed March 28, 2026, 3:08 p.m.
NEDg Description generation batch_69c7ef7f7b7c8190b3361cc01b2eefc0 completed March 28, 2026, 3:10 p.m.
NED2 Entity disambiguation (via description) batch_69c7f380dbe48190933e1eeff109185d completed March 28, 2026, 3:28 p.m.
Created at: March 27, 2026, 2:58 p.m.